Genai Adoption

Genai Adoption Data Jobs

6 jobs found

30d ago

Cloud AI Engineer, Lead

Zebra Technologies Lincolnshire, IL

Lincolnshire, IL

30d ago Closed

$97k - $145k/yr Full time AI Enablement Artificial Intelligence Automation

This position is no longer accepting applications (closed Aug 28, 2026).

Job Description

Zebra Technologies offers a hybrid work model with flexible hours, strong professional development opportunities, and a commitment to well being and inclusion. In the lead Cloud AI Engineer role, you will design, build, and scale cloud native AI platforms and AI powered tooling across IT Platform Engineering and Cloud Security. You will partner with stakeholders to translate ideas into concrete, rapid proofs of concept, delivering real value through hands on innovation. The role carries a competitive salary range and a robust benefits package designed to support you and your family.

Benefits

Hybrid work model with flexible hours
Summer Flex Fridays and Focus Fridays
Annual companywide well being day
Healthcare, wellness, and traditional insurances
Inclusion networks and ongoing learning and development
Community service days and parental leave
Employee assistance program and paid time off
Cash incentive programs
Compensation: USD 96,800 - 145,200 per year

Responsibilities

Identify and assess emerging opportunities across Platform Engineering and Cloud Infrastructure that align with business needs and cutting edge technology
Perform comprehensive business and systems analyses, translating complex findings into clear user stories, requirements, and actionable concepts
Lead and execute PoCs and hands on delivery to rapidly validate cloud and platform innovations
Research and report on disruptive technologies such as Generative AI, ML, RPA, and virtual agents, offering strategic recommendations for enterprise adoption
Serve as the primary IT Cloud Innovation Liaison, coordinating across innovation and product teams
Plan and facilitate structured ideation sessions to foster collaborative problem solving
Act as an Innovation Evangelist within IT and the broader enterprise to promote modern engineering practices
Track KPIs and provide leadership visibility into progress and business outcomes of innovation initiatives
Establish and maintain a repeatable operating model for cloud-native AI/ML deployment across GCP and Azure, focusing on pipeline architecture, performance, and compliance
Lead and mentor a high performing team of cloud and AI platform engineers toward predictive log analytics, automation (AIOps), and robust cloud data readiness
Translate AI governance, cloud security guardrails, and regulatory requirements into practical specs; integrate PII masking and RBAC into automated CI/CD pipelines
Manage roadmap alignment within the assigned technology portfolios

Requirements

Bachelor's degree in Computer Science, Electronic Engineering, Computer Engineering or a related field
5+ years in an operations style environment (NOC, SOC, MOC, etc.) with hands on troubleshooting of networking, service desk, operations center or cloud based infrastructure
Hands on Google Gemini Enterprise experience with the ability to build and deploy custom agents using the Agent Development Kit (ADK)
Multi cloud and GenAI platform proficiency including Google Cloud Platform (GCP), Azure, OpenAI, and Anthropic
Experience operating in global, heterogeneous cloud and on premises environments
Practical knowledge of large language models, Retrieval Augmented Generation architectures and agentic AI patterns such as Model Context Protocol, tool calling, and orchestration frameworks
Strong scripting or programming capability, particularly Python; software development background is a plus
Proven track record deploying containerized AI solutions using Kubernetes (GKE/AKS), Docker, and robust CI/CD with measurable outcomes such as high availability and latency reduction
Solid understanding of enterprise cloud security, API security, and fine grained identity systems; experience integrating PII masking and RBAC into automated pipelines
Active professional cloud certifications are highly preferred (eg Google Cloud Professional Cloud Architect, Professional ML Engineer or AI Engineer)
Strong Python based automation, infrastructure provisioning (IaC), and automated testing capabilities

Technologies

Google Gemini Enterprise
Agent Development Kit (ADK)
Google Cloud Platform (GCP)
Azure
OpenAI
Anthropic
Kubernetes (GKE/AKS)
Docker
Python

Location

This is a hybrid role requiring a minimum of three days per week on-site at either our Lincolnshire, IL or Holtsville, NY offices.

Preferred Qualifications

Some exposure to AI or ML systems, application security, or API security is a plus
Travel up to 10 percent

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1mo ago

Delivery Senior Consultant, Software Engineering Solutions, Identity & Gen AI Engineer

Deloitte Atlanta, GA

Atlanta, GA

1mo ago Closed

Full time Agentic Ai Artificial Intelligence Authentication

This position is no longer accepting applications (closed Aug 24, 2026).

Job Description

Deloitte is seeking a Delivery Senior Consultant specialized in Identity and Gen AI engineering to design, build, and secure AI solutions with identity, access, and trust controls across both human and non-human identities and GenAI platforms. This hands-on role blends engineering, integration, and continuous improvement to deliver secure and governable AI systems within a hybrid work setting in Atlanta.

Responsibilities

Build and integrate generative AI solutions, including LLM applications, retrieval-augmented generation, and AI agents, with secure data access and integration to downstream systems.
Engineer authentication, authorization, and identity controls for AI agents, service accounts, and other non-human identities across enterprise and cloud environments.
Develop guardrails for agentic workflows, including scoped permissions, least-privilege access, credential and secrets management, and runtime policy enforcement.
Implement logging, monitoring, and governance to provide traceability and accountability for AI system actions.
Collaborate with IAM, security architecture, and data teams to embed identity controls into GenAI solution delivery and operations.
Create and maintain reference architectures, reusable patterns, and technical documentation for building and securing AI systems.

Requirements

Bachelor's degree in Cybersecurity, Computer Science, Information Systems, Engineering, or a similar technical field.
Ability to work onsite up to five days per week.
3+ years of software engineering experience with Python or a comparable language.
1+ year of hands-on experience building, integrating, or deploying generative AI solutions such as LLM applications, retrieval-augmented generation, or AI agents, including use of model APIs, orchestration frameworks, and AI development tools (e.g., Claude Code, OpenAI Codex, GitHub Copilot, Cursor).
Working knowledge of identity and access management concepts and protocols, including authentication, authorization, SSO, and standards such as OpenID Connect (OIDC), SAML, OAuth, and JWT.
Ability to travel 15% on average, based on client and project needs.
Ability to obtain and maintain the necessary security clearance.
Legally authorized to work in the United States without the need for employer sponsorship now or in the future.
Delivery Center Location & Travel Requirements: Hybrid work model; residence within commutable distance to one of the US Delivery Center locations (Gilbert, Lake Mary, Mechanicsburg) or Geo-Hub locations (Atlanta, Charlotte, Dallas, Houston, Philadelphia).
Co-location up to 30% of working time at an assigned office for orchestrated opportunities, including projects, training, and related activities at Deloitte Delivery Center locations, Geo-Hub locations, approved sites, or project locations.
Travel requirement: Maximum of 10% overnight travel for client or project purposes.
Relocation: If required, move within 12 weeks to reside within commutable distance.

Technologies

Python
Claude Code
OpenAI Codex
GitHub Copilot
Cursor
LangChain
LangGraph
Model Context Protocol (MCP)
Open Policy Agent (OPA)
Cedar
OpenFGA
HashiCorp Vault
CyberArk
SailPoint
Okta
Microsoft Entra ID
AWS
Microsoft Azure
Terraform
Ansible
OpenID Connect (OIDC)
SAML
OAuth
JSON Web Token (JWT)

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1mo ago

Expert Consultant, Coro, AI Engineer

Bain & Co. Seattle, WA

Seattle, WA

1mo ago Closed

$129k - $172k/yr Full time Agentic Ai Ai Workflows Artificial Intelligence

This position is no longer accepting applications (closed Aug 21, 2026).

Job Description

Join Bain Coro as an Expert Consultant, AI Engineer, delivering GenAI powered tools and agentic AI workflows for B2B Commercial Excellence. This onsite role in Seattle spans projects from proof-of-concept to production deployments, translating AI innovation into measurable business outcomes. The position offers a competitive annual salary of USD 128,500 to 171,500, and requires 3–5+ years of AI/ML engineering experience along with a Bachelor’s degree in Computer Science or Engineering, or equivalent practical experience.

Benefits

Health insurance (medical, dental, and vision) with Bain paying 100% of individual premiums
Generous paid time off, including parental leave, sick leave, and paid holidays
Fully vested 401(k) company contribution
4.5% 401(k) company contribution (vesting after 3 years)
Life and Long-Term Disability insurance
Annual fitness reimbursements
Annual discretionary performance bonus

Responsibilities

Develop AI-enabled tools and products that deliver measurable business outcomes
Design and implement GenAI applications such as copilots, workflow automation, and decision support for commercial teams using modern LLM stacks
Implement agentic workflows with emphasis on reliability, safety, and clear failure modes, including tool use, multi-step execution, and human-in-the-loop controls
Architect and build advanced search, retrieval, and knowledge pipelines across diverse data stores (hybrid search, vector stores, graph databases / knowledge graphs, and traditional data platforms), addressing indexing, metadata, relevance tuning, freshness, caching, access controls, and source attribution
Develop robust agent capabilities including context engineering, memory and state management, orchestration, routing, and tool integration patterns
Integrate solutions into enterprise environments and workflows (APIs, data systems, collaboration tools), balancing quality, latency, cost, privacy, and adoption
Translate ambiguous client needs into clear technical requirements, tradeoffs, and delivery plans
Build and apply data science and machine learning capabilities end-to-end: data preparation, feature engineering, model selection, training, validation and testing, and performance analysis
Apply methods across classical ML and deep learning, including sequence, text, and image models when relevant
Create reproducible training and evaluation pipelines with versioning, experiment tracking, robust validation, and clear documentation
Demonstrate fluency with modern deep learning concepts, including transformer fundamentals and LLM pre-training versus post-training approaches
Write clean, testable, maintainable code and ship AI services through the full SDLC: build, test, deploy, monitor, and iterate
Implement MLOps and GenAIOps practices: CI/CD, reproducibility, environment parity, model/prompt/agent versioning, and operational readiness
Build evaluation and observability for GenAI and agentic systems: tracing, instrumentation, regression test suites, automated scoring where appropriate, and iteration loops for prompt and policy optimization
Design for secure enterprise deployment: access controls, auditability, data handling for sensitive and PII data, and responsible AI guardrails
Build reusable components and accelerators that scale across client contexts
Thrive in a client-facing consulting environment: communicate clearly with technical and non-technical stakeholders, lead sessions, present recommendations, and document technical details
Collaborate with Bain consultants to prioritize critical technical decisions that unlock business value and support proposal shaping and scoping

Requirements

3–5+ years of professional AI / ML engineering experience (or equivalent), with strong backend engineering fundamentals
Strong proficiency in Python and experience building APIs / services (REST / gRPC) and integrating with enterprise systems
Hands-on experience building LLM-powered applications with attention to latency, cost, reliability, and security
Experience building advanced retrieval / search systems (hybrid retrieval, vector search, reranking), and comfort working across vector, graph, relational, document, and search data stores
Experience implementing agentic patterns (context management, tool integration, orchestration, memory/state handling) with modern frameworks (LangGraph, OpenAI Agents SDK, Pydantic AI) or custom agent loops
Experience creating reusable skills, tools, and services (including MCP) for agent use, with schema validation (Pydantic) to enforce data contracts
Strong engineering practices: testing, code review, version control, CI/CD, and performance profiling
Experience deploying and operating services on AWS, GCP, and / or Azure, with focus on reliability and observability
Experience with Docker and Kubernetes and operating services in production
Proven ability to implement security, privacy, and governance requirements for AI systems, including authentication/authorization and PII handling
Experience training, validating, and testing ML models; solid understanding of overfitting, generalization, and evaluation methodology
Practical experience with feature engineering and data preprocessing for real-world datasets
Familiarity with a broad set of ML algorithms (classical and deep learning) and the ability to select appropriate methods
Familiarity with deep learning frameworks (PyTorch / TensorFlow) and ML lifecycle tooling (experiment tracking, model registry, feature store concepts)
Ability to operate effectively in ambiguity and complexity, manage priorities, and deliver outcomes independently or with a team
Excellent interpersonal and communication skills, with the ability to explain complex technical decisions to mixed audiences
Strong stakeholder management and client-facing capabilities
MBA or PhD in a technical field (preferred)
Background in consulting, professional services, or B2B analytics environments (preferred)
Experience collaborating with major AI ecosystem partners on real client deployments (preferred)

Technologies

Python
REST
gRPC
LangGraph
OpenAI Agents SDK
Pydantic AI
PyTorch
TensorFlow
Docker
Kubernetes
AWS
GCP
Azure
Vector stores
Graph databases
Knowledge graphs

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1mo ago

Expert Consultant, Coro, AI Engineer

Bain & Co. Washington, DC

Washington, DC

1mo ago Closed

$129k - $172k/yr Full time Python Advanced Analytics Agentic Ai

This position is no longer accepting applications (closed Aug 21, 2026).

Job Description

Join Bain & Company in Washington, DC, onsite, as an AI Engineer on the Coro team. You will help build GenAI powered tools and data-driven capabilities for B2B Commercial Excellence, designing, developing, and deploying AI solutions from proofs of concept to production in a client-facing consulting setting. This role centers on agentic workflows, retrieval pipelines, and ML models that drive business value for our clients.

This position offers a compelling benefits package and a collaborative culture that supports growth, impact, and professional development. You will work closely with Bain consultants and client teams to deliver practical AI solutions, balancing quality, speed, privacy, and adoption in enterprise environments.

Responsibilities

Design and build GenAI applications such as copilots, workflow automation, and decision-support tools for commercial teams using modern large language model stacks.
Implement agentic workflows with value, including tool use, multi-step execution, and human-in-the-loop controls, emphasizing reliability, safety, and clear failure modes.
Design and construct advanced search, retrieval, and knowledge pipelines across diverse data stores, covering indexing, metadata, relevance tuning, freshness, caching, access controls, and source attribution.
Develop robust agent capabilities including context engineering, memory and state management, orchestration, routing, and tool integration patterns.
Integrate AI solutions into enterprise environments and workflows (APIs, data systems, collaboration tools) while balancing quality, latency, cost, privacy, and adoption.
Translate ambiguous client needs into clear technical requirements, tradeoffs, and delivery plans.
Deliver end-to-end ML solutions: data preparation, feature engineering, model selection, training, validation, testing, and performance analysis.
Apply suitable methods spanning classical ML and deep learning, including sequence, text, and image models where relevant.
Create reproducible training and evaluation pipelines with versioning, experiment tracking, robust validation, and documentation.
Demonstrate fluency with modern deep learning concepts, including transformer fundamentals and LLM pre-training versus post-training approaches.
Write clean, testable, maintainable code and ship AI services through the full SDLC: build, test, deploy, monitor, and iterate.
Implement MLOps and GenAIOps practices: CI/CD, reproducibility, environment parity, model/prompt/agent versioning, and operational readiness.
Build evaluation and observability for GenAI and agentic systems: tracing, instrumentation, regression test suites, automated scoring, and iteration loops for prompt and policy optimization.
Design for secure enterprise deployment: access controls, auditability, handling of sensitive and PII data, and responsible AI guardrails.
Develop reusable components and accelerators that scale across client contexts, including templates, evaluation harnesses, connectors, and orchestration patterns.
Communicate clearly with technical and non-technical stakeholders; lead working sessions, present recommendations, and document technical approaches succinctly.
Collaborate with Bain consultants to prioritize technical decisions that unlock business value and support proposal shaping and scoping.

Requirements

Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
3-5+ years of professional AI / ML engineering experience with strong backend fundamentals.
Proficiency in Python and experience building APIs / services (REST / gRPC) and integrating with enterprise systems.
Hands-on experience delivering LLM powered applications with attention to latency, cost, reliability, and security.
Experience building advanced retrieval and search systems (hybrid retrieval, vector search, reranking) and working across vector, graph, relational, document, and search data stores.
Experience implementing agentic patterns (context management, tool integration, orchestration, memory/state handling) with modern frameworks (LangGraph, OpenAI Agents SDK, Pydantic AI) or custom agent loops; solid judgment on when to apply agentic approaches.
Experience creating reusable skills, tools, and services for agent use, with schema validation (Pydantic) to enforce reliable data contracts.
Strong engineering practices: testing, code review, version control, CI/CD, and performance profiling.
Experience deploying and operating services on AWS, GCP, and/or Azure, including environment management, reliability, observability, and scaling.
Experience with Docker and Kubernetes (or equivalents) and operating services in production (debugging, performance, resilience).
Proven ability to meet security, privacy, and governance requirements for AI systems (authentication/authorization, access controls, PII handling, enterprise risk controls).
Experience training, validating, and testing ML models with solid understanding of overfitting, generalization, and evaluation methodology.
Practical experience with feature engineering and data preprocessing for real-world datasets.
Familiarity with a broad set of ML algorithms (classical and deep learning) and the ability to select methods aligned with business constraints.
Familiarity with deep learning frameworks (PyTorch/TensorFlow) and ML lifecycle tooling (experiment tracking, model registry, feature store concepts).
Ability to operate effectively in ambiguous and complex environments, manage priorities, and deliver outcomes independently or with a team.
Excellent interpersonal and communication skills; able to explain technical decisions and results to mixed audiences.
Strong stakeholder management skills and comfort working directly with clients.

Technologies

Python
REST, gRPC
LangGraph
OpenAI Agents SDK
Pydantic AI
Docker
Kubernetes
AWS, GCP, Azure
PyTorch, TensorFlow
MCP

Compensation and Benefits

Base salary range of USD 128,500 to 171,500 annually, with variation by location and experience for states including Massachusetts, New York, District of Columbia, Georgia, Illinois, Texas, Washington, and California.
Annual discretionary performance bonus.
4.5% 401(k) company contribution, increasing after three years of service, fully vesting on start date.
Bain pays 100% of individual employee premiums for medical, dental, and vision coverage.
Generous paid time off including parental leave, sick leave, and holidays.
Paid life and long-term disability insurance.
Annual fitness reimbursements.
Other comprehensive benefits and wellness programs in line with Bain’s offerings.

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1mo ago

Senior AI Engineer - Guidewire

CNA Insurance Chicago, IL

Chicago, IL

1mo ago Closed

$72k - $141k/yr Full time Ai Governance Artificial Intelligence Engineer

This position is no longer accepting applications (closed Aug 14, 2026).

Job Description

CNA Insurance invites a senior AI engineer to join our Chicago area team in a hybrid role. This position centers on an AI first engineering transformation, steering the architecture and delivery of scalable AI enabled solutions across enterprise platforms, including Guidewire offerings. You will provide technical leadership and mentorship across teams, shaping engineering culture toward AI driven excellence. The role offers a competitive salary range of USD 72,000 to 141,000 per year and a path to influence engineering standards, governance, and productivity at scale.

Responsibilities

Define and advance the AI first engineering vision across development teams, promoting AI assisted development practices
Lead and mentor engineers in using AI tools responsibly and effectively (eg, GitHub Copilot, Claude, Developer Assistants)
Establish governance models and best practices for AI assisted development to ensure quality, security, compliance, and maintainability of generated code
Apply engineering judgment to review, validate, and standardize AI generated outputs
Architect and deliver scalable, cloud native, API driven solutions across enterprise platforms
Guide teams in building production grade applications using modern principles such as microservices, event driven architecture, and CI/CD
Accelerate development through AI assisted coding, testing, debugging, automation frameworks, reusable patterns, and improved developer tooling
Collaborate with business, product, architecture, and platform teams to align AI driven solutions with business outcomes
Drive integration strategies across enterprise systems using API first and event driven approaches
Provide technical oversight for complex programs and cross functional initiatives
Lead adoption of modern engineering practices including automation, observability, and test driven development
Evaluate and recommend emerging technologies in AI, automation, and developer productivity
Support production readiness, troubleshooting, and continuous improvement of application performance and reliability
(Preferred) Contribute to or guide implementations involving Guidewire InsuranceSuite and Digital Solutions
Mentor engineers and foster a culture of continuous learning, innovation, and AI driven excellence
May perform additional duties as assigned

Requirements

Proven experience driving AI assisted development practices at scale
Hands on experience with Claude, GitHub Copilot, Cursor, or similar tools
Strong ability to evaluate and govern AI generated code
Demonstrated ability to define standards, frameworks, and best practices
Experience mentoring teams and enabling AI adoption across engineering organizations
Strong understanding of secure coding and compliance in AI enabled environments
Strong expertise in cloud native architecture, microservices, and distributed systems
Experience with API first, integration, and event driven architectures
Proven ability to build scalable, production grade applications
Familiarity with DevOps, CI/CD, and automation frameworks
Full stack development expertise (Java/J2EE or similar stack, microservices, UI frameworks)
Strong knowledge of API design, integration platforms, and web services
Excellent problem solving and decision making skills
Experience with Guidewire InsuranceSuite and Digital
Exposure to Guidewire Cloud Platform and integration patterns
Understanding of the P&C insurance domain
Experience with Guidewire Jutro Digital Platform (JDP) is a plus
Strong leadership, communication, and stakeholder management skills
Ability to influence without authority and drive change across teams
Strong collaboration across distributed and cross functional teams

Technologies

GitHub Copilot, Claude, Cursor
Guidewire InsuranceSuite, Guidewire Digital Solutions
Guidewire Cloud Platform, Guidewire Jutro Digital Platform (JDP)
Java/J2EE, UI frameworks

Reporting relationship

Typically Director or above

AI Engineering & Leadership

Proven experience driving AI assisted development practices at scale
Hands on experience with Claude, GitHub Copilot, Cursor, or similar
Strong ability to evaluate and govern AI generated code
Demonstrated ability to define standards, frameworks, and best practices
Experience mentoring teams and enabling AI adoption across engineering organizations
Strong understanding of secure coding and compliance in AI enabled environments

Architecture & Modern Engineering

Strong expertise in cloud native architecture, microservices, and distributed systems
Experience with API first, integration, and event driven architectures
Proven ability to build scalable, production grade applications
Familiarity with DevOps, CI/CD, and automation frameworks

Technical Skills

Full stack development expertise (Java/J2EE or similar stack, microservices, UI frameworks)
Strong knowledge of API design, integration platforms, and web services
Excellent problem solving and decision making skills

Guidewire & Domain (Preferred / Nice to Have)

Experience with Guidewire InsuranceSuite and Digital
Exposure to Guidewire Cloud Platform and integration patterns
Understanding of the P and C insurance domain
Experience with Guidewire Jutro Digital Platform (JDP) is a plus

Soft Skills

Strong leadership, communication, and stakeholder management skills
Ability to influence without authority and drive change across teams
Strong collaboration across distributed and cross functional teams

Role differentiators

Focus on AI first engineering transformation rather than solely development
Combines hands on engineering with leadership and vision setting
Opens opportunities to influence engineering culture, standards, and delivery models
Flexible application of AI engineering practices across multiple platforms, not limited to Guidewire

Education & Experience

Bachelor's degree in computer science or related discipline or equivalent experience
Typically 8+ years of software engineering experience including AI assisted development
Experience in technical leadership, architecture, or team enablement roles
Experience in enterprise platforms or insurance domain is a plus
Prior exposure to Guidewire implementations preferred but not required

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1mo ago

Senior AI Engineer

CNA Insurance Chicago, IL

Chicago, IL

1mo ago Closed

$72k - $141k/yr Full time Senior AI Enablement Artificial Intelligence

This position is no longer accepting applications (closed Aug 13, 2026).

Job Description

At CNA Insurance, the Senior AI Engineer role sits at the crossroads of software delivery and intelligent tooling. Based in Chicago with a hybrid work arrangement, this position leads the architectural design and integration of AI-powered engineering platforms across the CNA engineering community, helping teams embed AI capabilities into their dev and test workflows. The role offers a salary range of USD 72,000 to 141,000 per year and requires at least seven years of relevant experience, along with a Bachelor’s degree in Computer Science or a related discipline, or equivalent work experience.

Responsibilities

Oversee the architecture, design, development, and integration of AI-enabled engineering platforms, applications, agents, and capabilities that support software delivery and boost developer productivity.
Advance adoption of AI-powered development platforms across the engineering community through road shows, communities of practice, and demonstration sessions.
Offer technical leadership and consultation on AI solution design, application integration, prompt and workflow patterns, and secure, scalable implementation approaches.
Develop and implement robust testing and validation strategies for AI-enabled applications and platforms, including automated testing, quality assurance processes, and CI/CD integration.
Research, evaluate, and recommend AI tools, frameworks, models, and platform capabilities to identify effective and cost-efficient solutions aligned with business and engineering needs.
Collaborate with engineering, infrastructure, security, testing teams, and external partners to align requirements, integrate solutions, and ensure successful delivery of AI platform capabilities.
Contribute to AI engineering strategy, architecture direction, governance, and best practices, including reusable patterns for platform development, integration, observability, and supportability.
Support deployment, monitoring, issue resolution, and ongoing enhancement of AI-based applications and platforms in test and production environments to ensure reliability, performance, and continuous improvement.

Requirements

Solid knowledge of AI-native development tools such as Cursor, GitHub Copilot, Claude Code, and MCPs.
Strong technical capability for developing AI-based platforms, applications, agents, and skills.
Experience developing EVALs and Observability platforms for AI-native solutions.
Experience with AI model development and app design, specifically Vertex AI.
Experience with Retrieval-Augmented Generation (RAG) pipeline architecture and development.
Proficiency in high-level programming languages such as Python and/or TypeScript, Java, or JavaScript.
Solid understanding of programming languages, databases, interfaces, and familiarity with alternative application development approaches.
Advanced knowledge in designing and building integration platforms, APIs, and web services.
Five or more years of experience with development tools including VS Code or JetBrains IDEs, Git and GitHub, npm/yarn, pip, Maven/Gradle, and Docker.
Experience in AI-native system development life cycle and alternative technologies for application development.
Understanding of state-of-the-art application development support software packages.
Proficiency in at least one high-level programming language.
Strong analytical and problem-solving abilities.
Excellent communications and interpersonal skills with the ability to collaborate with peers, IT leadership, staff, and external partners.
Ability to manage projects, lead teams, and mentor colleagues.
Preferred: insurance industry knowledge.
Preferred: experience with React or other front-end frameworks.
Preferred: experience as an SDET or strong knowledge of test automation tools such as Playwright or Cypress.
Bachelor's degree in Computer Science or related discipline, or equivalent work experience.
Typically at least seven years of systems analysis and application development experience, plus some project leadership experience.
Applicable certifications preferred.

Technologies

Cursor
GitHub Copilot
Claude Code
MCPs
Vertex AI
RAG (Retrieval-Augmented Generation)
Python
TypeScript
Java
JavaScript
VS Code
JetBrains IDEs
Git
GitHub
npm
yarn
pip
Maven
Gradle
Docker
Playwright
Cypress
React

Reporting relationship

Typically Director or above

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Genai Adoption Data Jobs

Cloud AI Engineer, Lead

Delivery Senior Consultant, Software Engineering Solutions, Identity & Gen AI Engineer

Expert Consultant, Coro, AI Engineer

Expert Consultant, Coro, AI Engineer

Senior AI Engineer - Guidewire

Senior AI Engineer

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