Cloud Infrastructure

Cloud Infrastructure Data Jobs

19 jobs found

Today

Machine Learning Engineer - Document Digitization (LLMs)-Vice President

JPMorganChase Jersey City, NJ

Jersey City, NJ

Today

$164k - $260k/yr Full time Ai Ml Amazon Eks Artificial Intelligence

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Job Description

Senior Vice President level Machine Learning Engineer at JPMorgan Chase, focusing on designing, building, and deploying AI powered document digitization solutions with LLMs in Jersey City, NJ (onsite).

Responsibilities

Lead the design, development, and integration of AI powered document digitization solutions to extract information from diverse document types.
Oversee the end-to-end AI/ML lifecycle: training, validation, deployment, monitoring, and production grade continuous improvement.
Apply generative AI and large language models to automate and optimize document workflows.
Build and maintain scalable digitization pipelines using Python, AI frameworks, and cloud technologies.
Provision and manage cloud resources with infrastructure as code tools (Terraform) and AWS services such as SageMaker and Bedrock.
Ensure scalability, reliability, security, and governance compliance of AI/ML solutions.
Collaborate with cross functional teams to reimagine legacy document processing using generative AI and LLMs.
Develop dashboards and reporting tools to monitor digitization accuracy, workflow efficiency, and business impact.
Mentor junior engineers and promote best practices in AI/ML, software engineering, and testing.
Conduct model validation, human in the loop reviews, and implement continuous improvement strategies for digitization accuracy.
Contribute to communities of practice and explore new and emerging technologies.

Requirements

Bachelor's or Master's in Computer Science, Data Science, Machine Learning, or a related field with relevant industry experience.
Strong proficiency in Python for building production grade AI services and data/document pipelines.
Strong working proficiency in Java, including API and microservice development with Spring Boot; familiarity with front end technologies (React.js, AngularJS) is a plus.
Hands-on experience delivering LLM powered or GenAI applications in production (document understanding, retrieval augmented generation, workflow automation) including evaluation, observability, guardrails, and continuous improvement.
Experience with MLOps / LLMOps practices in production environments (CI/CD, automated testing, deployment strategies, monitoring, incident response).
Working knowledge of machine learning frameworks (TensorFlow, PyTorch, Scikit-learn, PyTorch Lightning) focused on integrating models and services into scalable systems.
Experience with AWS and cloud native delivery, including SageMaker and/or Bedrock, containerization (Docker, Kubernetes, Amazon EKS), and infrastructure as code (Terraform).
Familiarity with NoSQL / search / graph technologies (MongoDB Atlas, Elasticsearch/OpenSearch, Neo4j) and their use in document search and knowledge retrieval.
Experience with agentic coding approaches, autonomous/assisted code agents, orchestration patterns, and tool-use/agent frameworks to accelerate digitization workflows.
Strong understanding of SDLC, CI/CD, resiliency, and security practices; proven problem solving, communication, and collaboration skills.
Demonstrated ability to accelerate development using AI technologies while maintaining engineering rigor (testing, code quality, governance).

Technologies

Python
Terraform
AWS SageMaker
AWS Bedrock
Docker
Kubernetes
Amazon EKS
Java
Spring Boot
React.js
AngularJS
TensorFlow
PyTorch
Scikit-learn
PyTorch Lightning
MongoDB Atlas
Elasticsearch/OpenSearch
Neo4j
LLMs

Benefits

Equity/stock-based compensation
Competitive base salary
Commission-based pay and/or discretionary incentive compensation
Comprehensive health care coverage
On-site health and wellness centers
Retirement savings plan
Backup childcare
Tuition reimbursement
Mental health support
Financial coaching

About JPMorganChase

JPMorganChase is a long standing financial services institution serving consumers, small businesses, and large organizations worldwide under the J.P. Morgan and Chase brands. With a history spanning more than 200 years, the firm leads in investment banking, consumer and small business banking, commercial banking, payments processing, and asset management.

About the Team

Corporate Functions teams cover a broad range of areas from finance and risk to human resources and marketing. These professional groups play a key role in enabling business success for clients, customers, and employees across the organization.

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Today

Staff Data Engineer

Okta Chicago, IL

Chicago, IL

Today

$174k - $239k/yr Full time Senior Apache Airflow Cloud

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Job Description

Okta is seeking a Staff Data Engineer to join the Auth0 Data Engineering Team in Chicago, IL on a hybrid schedule. This role leads the architectural evolution of the core data platform, starting with FEDRamp compliance, and drives scalable, secure designs across multiple teams. The position offers a salary range of USD 174,000 to 238,700 per year, with benefits that emphasize well-being, social impact, and talent development within a collaborative culture.

Benefits

Supporting Your Well-Being
Driving Social Impact
Developing Talent and Fostering Connection + Community

The Auth0 Data Engineering Team

Pipeline team — sits near the Platform team and data producers, responsible for efficient data ingestion and rapid access to unmodeled data
Warehouse team — aligns with business teams and data consumers, modeling data in the data warehouse to abstract complexity and simplify analysis, reporting, and decision-making
Interface team — builds and manages connections between the data platform and external systems to ensure consistent and reliable data access

Responsibilities

Spearhead the evolution of the core data platform, shaping the long-term architectural roadmap
Set the technical direction for large-scale platform improvements, balancing visionary goals with incremental delivery
Collaborate with engineers and leaders across data, platform, and security to deliver a cohesive and secure architecture
Create architectural artifacts such as design documents, threat models, and technical specifications to drive clarity and alignment on complex initiatives
Serve as a technical mentor and multiplier for the Data Engineering team, elevating performance through guidance, code reviews, and sharing best practices
Build foundational components of the new architecture, validating designs with hands-on coding and serving as a model for other engineers

Requirements

A passion for building secure, reliable, and scalable data systems
8+ years of software development experience, with at least 5+ years in a data engineering or data platform role
Proven experience designing and delivering large-scale, cross-functional technical projects
Extensive experience architecting and deploying data infrastructure in a cloud environment, with AWS strongly preferred
Deep architectural knowledge of the modern data stack, including data warehouses (Snowflake), transformation tools (dbt), and orchestrators (Airflow)
Strong proficiency in Python and SQL, with a high bar for code quality and system design
Excellent communication skills, with the ability to create clarity and drive decisions on complex technical topics
Ability to deal with ambiguity, define a path forward, and lead others to successful outcomes

Technologies

Technologies: Snowflake, dbt, Airflow, Python, SQL, AWS, Terraform, Kubernetes

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Today

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

Deloitte Atlanta, GA

Atlanta, GA

Today

Full time Agentic Ai Artificial Intelligence Authentication

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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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1d ago

AWS AI Engineer

Hudson Manpower San Jose, CA 🇺🇸 Remote

San Jose, CA

1d ago

Full time AI Ai Workflows Artificial Intelligence

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Job Description

Hudson Manpower is seeking a Senior AWS AI Engineer to lead the hands-on development of AI and ML applications within AWS, with a focus on retrieval-augmented generation, fine-tuning LLMs, and enterprise-grade microservices for automation and governance.

Responsibilities

Hands-on practitioner leveraging AWS core services including Lambda, Bedrock, SageMaker, Step Functions, DynamoDB, and S3.
Owns the implementation of AWS cloud services spanning infrastructure, machine learning, and AI platform services.
Develops LLM-based applications, including Retrieval-Augmented Generation (RAG) using LangChain and related frameworks.
Builds cloud-native microservices, APIs, and serverless functions to enable intelligent automation and real-time data processing.
Collaborates with internal stakeholders to translate business goals into secure, scalable AI systems.
Owns the software release lifecycle, including CI/CD pipelines, GitHub based SDLC, and infrastructure as code with Terraform.
Supports the development and evolution of reusable platform components for AI/ML operations.
Creates and maintains technical documentation for the team and internal customers.
Excellent verbal and written communication in English.

Requirements

Minimum seven years of hands-on software engineering experience with strong Python expertise.
Proficiency with AWS services, notably Bedrock and SageMaker.
Experience fine-tuning large language models or building datasets and deploying ML models to production.
Experience with AWS Organizations and policy guardrails such as SCPs and AWS Config.
Strong background in RAG architectures and LangChain.
Proven infrastructure as code practices and Terraform module development for AWS.
Solid Git-based version control, code reviews, and DevOps workflows.
Track record of delivering production-ready software with integrated release pipelines.

Technologies

Python
Bedrock
SageMaker
Lambda
Step Functions
DynamoDB
S3
LangChain
Transformers
PyTorch
TensorFlow
Terraform
Terraform Sentinel
GitHub
Hugging Face
Node.js
Golang
AWS
SCP
AWS Config

Benefits

Competitive base salary
Medical, dental, and vision insurance coverage
Optional life and disability insurance provided
401(k) with company match and optional profit sharing
Paid vacation time
Paid bench time
Training allowance offering
Eligible for referral bonuses

Supervisory Responsibilities

None

Nice-to-Haves

AWS or relevant cloud certifications
Policy as Code development experience such as Terraform Sentinel
Experience with Hugging Face, Golang, or Node.js
Exposure to FinOps and cloud cost optimization
Data science background or experience with structured and unstructured data
Awareness of data privacy and compliance best practices including PII handling and secure model deployment

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1d ago

Data Engineer II (AWS, Python, SQL)

Travelers Hartford, CT

Hartford, CT

1d ago

$127k - $209k/yr Full time Actuarial Automation CI/CD

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Job Description

Data Engineer II at Travelers focuses on building data pipelines and production-ready data solutions for Property and General Liability pricing, collaborating with actuarial and data science teams using AWS, Python, and SQL.

Responsibilities

Own end-to-end development and ongoing support of data pipelines for Property and GL pricing use cases
Lead model implementation for Property and GL pricing in partnership with Data Science and Actuarial teams
Serve as the GL data subject matter expert to support benchmarks, modernization efforts, and future enhancements
Provide project leadership, planning, and execution across Property and GL data engineering initiatives
Execute complex data preparation tasks including exploration, cleansing, and transformation with awareness of enterprise architecture, platforms, and downstream consumption patterns
Translate actuarial and data science requirements into scalable, production-ready data solutions
Adopt and embed MLOps practices across the model development and implementation lifecycle
Establish data quality controls, profiling, and monitoring for model implementation and ongoing performance
Present analysis and technical recommendations to influence data architecture and implementation decisions
Provide technical leadership through code reviews, design guidance, and mentoring within the team
Apply agile methodologies to plan, prioritize, and deliver work across concurrent initiatives
Perform other duties as assigned

Requirements

Bachelor’s degree in a STEM field or equivalent
Eight years of related experience
Cloud platforms experience, preferably AWS, with cloud-based model implementations
Proficiency in Python and SQL
Experience with data engineering concepts and building and maintaining data pipelines
Experience delivering AI-native solutions and modern software engineering practices (APIs, microservices, test automation)
Ability to break work into small, releasable increments and deliver robust solutions while balancing tradeoffs
Strong understanding of technical concepts and industry trends with deep knowledge of the systems worked on
Excellent problem-solving skills and the ability to build resilient, long-lived systems with innovative issue resolution
Excellent written and verbal communication; ability to collaborate with engineers, product partners, and business stakeholders
Proven experience mentoring engineers and fostering an inclusive environment for learning and growth
Self-motivated with a track record of identifying opportunities, driving improvements, and following through on team initiatives

Technologies

AWS
Python
SQL
Terraform
CI/CD

Location

Hartford, CT onsite

Compensation

Salary range: USD 126,500 - 208,700 per year

Benefits

Health Insurance
Retirement
Paid Time Off
Wellness Program
Volunteer Encouragement

What is the opportunity?

In this role, you will influence pricing outcomes for Business Insurance Property and General Liability by turning analytical ideas into trusted, production-grade data assets. You will collaborate with Actuarial and Data Science partners, deepen domain expertise in Property and GL, and contribute to modernization and forward-looking pricing capabilities.

Employment Practices

Travelers is an equal opportunity employer. We value the unique abilities and perspectives each person brings to the organization.

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2d ago

AWS AI Engineer

Hudson Manpower Buffalo Grove, IL 🇺🇸 Remote

Buffalo Grove, IL

2d ago

Full time AI Amazon Web Services Artificial Intelligence

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Job Description

Hudson Manpower is looking for a Senior AWS AI Engineer to design and deliver production-grade AI and ML services on AWS, with a focus on retrieval-augmented generation and fine-tuning large language models. The role supports enterprise automation and governance through AWS-native microservices, enabling scalable AI solutions across business processes. This position is based in Buffalo Grove, Illinois, with remote work options available.

Responsibilities

Direct, hands-on work with AWS services including Lambda, Bedrock, SageMaker, Step Functions, DynamoDB, and S3.
Implement AWS cloud services spanning infrastructure, machine learning, and AI platform offerings.
Develop LLM-based applications, incorporating Retrieval-Augmented Generation (RAG) with LangChain and related frameworks.
Build cloud-native microservices, APIs, and serverless functions to enable intelligent automation and real-time data processing.
Partner with internal stakeholders to translate business goals into secure, scalable AI systems.
Own the software release lifecycle, including CI/CD pipelines, GitHub-based SDLC, and infrastructure as code with Terraform.
Support the development and evolution of reusable platform components for AI/ML operations.
Create and maintain technical documentation for the team and internal customers.
Communicate effectively in English, both verbally and in writing.

Requirements

7 years of hands-on software engineering experience with a strong focus on Python.
Experience with AWS services, especially Bedrock, SageMaker, ECS, and Lambda.
Familiarity with AWS Organizations and policy guardrails (SCP, AWS Config).
Experience with Retrieval-Augmented Generation (RAG) architectures and using LangChain and similar frameworks.
Proficiency in fine-tuning large language models, building datasets, and deploying ML models to production.
Strong background in Infrastructure as Code best practices with experience building Terraform modules for AWS.
Solid experience with Git-based version control, code reviews, and DevOps workflows.
Proven track record of delivering production-ready software with release pipeline integration.

Technologies

Python
AWS Bedrock, SageMaker, ECS, Lambda
AWS Organizations, SCP, AWS Config
LangChain
Transformers, PyTorch, TensorFlow
Terraform, Terraform Sentinel
AWS Step Functions, DynamoDB, S3
Hugging Face
Node.js, Golang
GitHub

Benefits

Competitive base salary
Medical, dental, and vision insurance coverage
Optional life and disability insurance
401(k) with company match and optional profit sharing
Paid vacation time
Paid bench time
Training allowance
Referral bonuses

Minimum Knowledge, Skills, and Abilities Required

7 years of hands-on software engineering experience with a strong emphasis on Python.
Experience with AWS services, particularly Bedrock or SageMaker.
Familiarity with fine-tuning large language models or building datasets and deploying ML models to production.
Experience with AWS Organizations and policy guardrails (SCP, AWS Config).
Solid background in implementing RAG architectures and LangChain.
Experience with Infrastructure as Code practices and Terraform module development for AWS.
Strong Git-based version control, code reviews, and DevOps workflows.
Demonstrated success delivering production-ready software with release pipeline integration.

Nice-To-Haves

AWS or relevant cloud certifications
Policy as Code development such as Terraform Sentinel
Experience with Hugging Face, Golang, or Node.js
Exposure to FinOps and cloud cost optimization
Data science background or experience with structured and unstructured data
Awareness of data privacy and compliance best practices (PII handling, secure model deployment)

What You’ll Get

Competitive base salary
Medical, dental, and vision insurance coverage
Optional life and disability insurance
401(k) with company match and optional profit sharing
Paid vacation time
Paid bench time
Training allowance
Eligibility for referral bonuses

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2d ago

AWS AI Engineer

Hudson Manpower Pittsburgh, PA 🇺🇸 Remote

Pittsburgh, PA

2d ago

Full time AI Amazon Web Services Artificial Intelligence

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Job Description

Hudson Manpower is seeking a Senior AWS AI Engineer to architect and operate production AI/ML applications on AWS, with a focus on retrieval-augmented generation, fine-tuning large language models, and cloud-native microservices. The role centers on delivering secure AI services that integrate with live infrastructure data, built to scale and operate within live environments. The position is based in Pittsburgh, PA with remote work options and requires seven years of hands-on software engineering experience.

Responsibilities

Hands-on work with AWS services including Lambda, Bedrock, SageMaker, Step Functions, DynamoDB, and S3 to implement cloud infrastructure, machine learning features, and AI platform capabilities.
Own the deployment of AWS cloud services, spanning infrastructure, ML workflows, and AI platform services.
Develop and maintain LLM based applications, including Retrieval-Augmented Generation (RAG) using LangChain and related frameworks.
Build cloud-native microservices, APIs, and serverless functions to enable intelligent automation and real-time data processing.
Collaborate with internal stakeholders to translate business goals into secure, scalable AI systems.
Manage the software release lifecycle, including CI/CD pipelines, GitHub-based SDLC, and infrastructure as code with Terraform.
Support a reusable set of platform components for AI/ML operations and their evolution.
Create and maintain technical documentation for the team and internal customers.
Provide clear verbal and written communication in English.

Requirements

Seven years of hands-on software engineering experience with a strong emphasis on Python.
Experience with AWS services, particularly Bedrock or SageMaker.
Familiarity with fine-tuning large language models or building datasets and deploying ML models to production.
Experience navigating AWS organizations and policy guardrails such as SCP and AWS Config.
Solid track record implementing RAG architectures and using LangChain.
Proven experience with Infrastructure as Code best practices and building Terraform modules for AWS.
Strong background in Git-based version control, code reviews, and DevOps workflows.
Proven success delivering production-ready software with release pipeline integration.

Technologies

Python, Bedrock, SageMaker
ECS, Lambda, Step Functions
DynamoDB, S3
LangChain, Transformers, PyTorch, TensorFlow
Terraform, Git, GitHub
Hugging Face, Node.js, Golang
Terraform Sentinel, AWS Config, SCP

Benefits

Competitive base salary
Medical, dental, and vision insurance coverage
Optional life and disability insurance
401(k) with company match and optional profit sharing
Paid vacation time
Paid bench time
Training allowance
Referral bonuses

Top Skills

Experience with AWS services including Bedrock, SageMaker, ECS, and Lambda
Strong knowledge of AWS organizations and policy guardrails (SCP, AWS Config)
Proficiency in implementing RAG architectures and using ML tooling such as Transformers, PyTorch, TensorFlow, and LangChain
Infrastructure as Code best practices and building Terraform modules for AWS
Fine-tuning large language models, building datasets, and deploying ML models to production
Git-based version control, code reviews, and DevOps workflows
AWS or relevant cloud certifications
Data privacy and compliance best practices, including secure model deployment
Data science background or experience with structured and unstructured data
Exposure to FinOps and cloud cost optimization
Hugging Face, Node.js
Policy as Code development (Terraform Sentinel)