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4 jobs found

Today

Senior Manager, AI Engineer Intelligence Layer

Alvarez and Marsal New York, NY

New York, NY

Today

$190k - $210k/yr Full time Backend Developer Manager Senior

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Job Description

Alvarez and Marsal is building an Intelligence Layer that makes the firm’s knowledge securely available for global and business-unit-specific search and AI experiences. In this onsite role in New York, you will help design and deliver the knowledge graph platform, working from architecture and ingestion through retrieval, APIs, and production agentic pipelines.

What you will do

Build and maintain components of the Intelligence Layer, including ingestion pipelines, knowledge graph models, retrieval services, APIs, and user-facing capabilities.
Develop and optimize graph schemas and queries using Neo4j and Cypher (or comparable graph technologies).
Contribute across the stack with strong Python and back-end development skills, while supporting modern front-end development when needed.
Integrate structured data and unstructured content from enterprise systems while preserving source permissions, metadata, and governance requirements.
Build integrations with large language model platforms and apply the Model Context Protocol (MCP) so Intelligence Layer capabilities can be used by approved AI tools.
Build, test, and operate production agentic pipelines, including multi-step orchestration, tool routing, MCP-based tool use, retrieval, state management, evaluation, guardrails, observability, and human-in-the-loop controls.
Partner with the Lead and Architect and delivery partners on implementation, testing, debugging, code review, and technical documentation.
Develop secure, maintainable software that supports client confidentiality, access control, reliability, and observability.
Communicate risks and blockers early and help the team make practical technical decisions as priorities evolve.
Help deliver the initial production iteration of the Intelligence Layer knowledge graphs.
Help deliver reusable agentic pipeline components for secure, governed workflows across business units and use cases.
Enable global search and business unit specific search across approved structured and unstructured data sources.
Deliver tested ingestion, graph, retrieval, API, and user-interface components that internal teams can operate and extend.
Establish reusable engineering patterns and documentation that support additional business units and data sources.

First-year outcomes

Deliver the initial production iteration of the Intelligence Layer knowledge graphs.
Deliver reusable agentic pipeline components supporting secure, governed workflows across business units and use cases.
Enable global search and business unit specific search across approved structured and unstructured data sources.
Ship tested ingestion, graph, retrieval, API, and user-interface components internal teams can operate and extend.
Establish reusable engineering patterns and documentation to support additional business units and data sources.

Required qualifications

Five or more years of software engineering experience building production applications or data platforms.
Hands-on experience with knowledge graphs, graph data modeling, and graph query languages, ideally Neo4j and Cypher.
Full-stack development experience with strong Python and back-end skills, plus working experience with a modern front-end framework.
Experience designing, building, and consuming APIs and integrating multiple structured and unstructured data sources.
Practical experience with Claude, ChatGPT, or comparable large language model platforms.
Hands-on experience building production agentic pipelines or workflows, including orchestration, tool use, retrieval, state management, evaluation, guardrails, observability, or human oversight.
Working knowledge of the Model Context Protocol, including how MCP servers expose tools and data to AI clients.
Experience working directly with third-party delivery vendors on implementation, technical review, issue resolution, and delivery coordination.
Strong problem-solving, communication, and documentation skills.
Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.

Preferred qualifications

Hands-on experience building MCP servers, agent tools, or custom AI integrations.
Experience with Microsoft Azure services for application hosting, data, search, identity, or AI.
Experience implementing enterprise authentication and authorization using Microsoft Entra ID, OAuth 2.0, OpenID Connect, token scoping, or on-behalf-of flows.

Technologies

Neo4j, Cypher, Python
Claude, ChatGPT, Model Context Protocol, MCP servers, large language model platforms
Microsoft Azure
Microsoft Entra ID, OAuth 2.0, OpenID Connect
Token scoping, on-behalf-of flows

Compensation

The salary range is $190,000 - $210,000 annually, dependent on education, experience, skills, and geography. A discretionary bonus program may also be available based on individual and firm performance. Please ask your recruiter for details.

Benefits

Healthcare plans
Flexible spending and savings accounts
Life, AD&D, and disability coverages
401(k) retirement savings plan
Annual discretionary contribution to their 401(k) retirement savings plan
Paid time off including vacation, personal days, seventy-two (72) hours of sick time (prorated for part time employees), ten federal holidays, one floating holiday, and parental leave
Click here for more information regarding A&M's benefits programs.

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Today

Senior Manager, AI Engineer Intelligence Layer

Alvarez & Marsal Chicago, IL

Chicago, IL

Today

$190k - $210k/yr Full time Backend Developer Manager Senior

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Job Description

Alvarez & Marsal is hiring a Senior AI Engineer to build and scale the Intelligence Layer, an A&M knowledge-graph-based platform that securely makes structured and unstructured knowledge available through search experiences. This role combines platform engineering with AI integration and agentic workflow development, with a focus on secure access, governance, and production reliability.

Location: Chicago, IL (onsite) | Salary: USD 190,000 - 210,000 per year

What you’ll build

Components of the Intelligence Layer, including ingestion pipelines, knowledge graph models, retrieval services, APIs, and user-facing capabilities.
Graph schemas and queries using Neo4j and Cypher (or comparable graph technologies).
Integrations that connect enterprise structured data and unstructured content, while preserving source permissions, metadata, and governance requirements.
LLM integrations, including applying the Model Context Protocol (MCP) so Intelligence Layer capabilities are available to approved AI tools.
Production-grade agentic pipelines with multi-step orchestration, tool routing, MCP-based tool use, retrieval, state management, evaluation, guardrails, observability, and human-in-the-loop controls.
Secure, maintainable software that supports client confidentiality, access control, reliability, and observability.

How the work is delivered

Partner with the Lead and Architect and delivery partners on implementation, testing, debugging, code review, and technical documentation.
Communicate risks and blockers early and help the team make practical technical decisions as priorities evolve.

What you bring

5+ years of software engineering experience building production applications or data platforms.
Hands-on experience with knowledge graphs, graph data modeling, and graph query languages, ideally Neo4j and Cypher.
Full-stack development experience with strong Python and back-end skills, plus working experience with a modern front-end framework (React is listed).
Experience designing, building, and consuming APIs and integrating multiple structured and unstructured data sources.
Practical experience with Claude, ChatGPT, or comparable large language model platforms.
Hands-on experience building production agentic pipelines or workflows, including orchestration, tool use, retrieval, state management, evaluation, guardrails, observability, or human oversight.
Working knowledge of Model Context Protocol, including how MCP servers expose tools and data to AI clients.
Experience working directly with third-party delivery vendors on implementation, technical review, issue resolution, and delivery coordination.
Strong problem-solving, communication, and documentation skills.
Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent practical experience).

Technologies you’ll use

Neo4j, Cypher, Python
Large language model platforms, Claude, ChatGPT
Model Context Protocol (MCP)
OAuth 2.0, OpenID Connect, Microsoft Entra ID, Microsoft Azure
React, APIs, agentic pipelines

Benefits

Healthcare plans, flexible spending and savings accounts, life, AD&D, and disability coverages for regular employees working 30+ hours per week.
401(k) retirement savings plan, including an annual discretionary contribution when eligibility requirements are met.
Paid time off including vacation, personal days, seventy-two (72) hours of sick time (prorated for part-time employees), ten federal holidays, one floating holiday, and parental leave.

First-year outcomes

Support delivery of the initial production iteration of the Intelligence Layer knowledge graphs.
Deliver reusable agentic pipeline components supporting secure, governed workflows across business units and use cases.
Enable global search and business unit specific search across approved structured and unstructured data sources.
Ship tested ingestion, graph, retrieval, API, and user-interface components internal teams can operate and extend.
Establish reusable engineering patterns and documentation to expand to additional business units and data sources.

Preferred qualifications

Hands-on experience building MCP servers, agent tools, or custom AI integrations.
Experience with Microsoft Azure services for application hosting, data, search, identity, or AI.
Experience implementing enterprise authentication and authorization using Microsoft Entra ID, OAuth 2.0, OpenID Connect, token scoping, or on-behalf-of flows.

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6d ago

Agentic AI Engineer

United Contractor Services Kennesaw, GA

Kennesaw, GA

6d ago

Full time Backend Developer Agent Orchestration Agentic Ai

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Job Description

United Contractor Services is building production-grade agentic AI to automate business processes across the organization’s Microsoft and Azure ecosystem. As an on-site Agentic AI Engineer in Kennesaw, GA, you will design, ship, and maintain AI agents that combine tool calling, orchestration, and production governance, with evaluation and observability built in.

You’ll work with leadership and operators to identify high-value automation opportunities, then translate them into delivered agent systems and integrations. The focus is practical engineering: secure identity and authorization, rigorous eval pipelines, and dependable agent operations in real production environments.

Responsibilities

Design and build production agentic AI systems including tool calling, multi-step reasoning, sub-agent orchestration, memory, retrieval, and human-in-the-loop checkpoints.
Collaborate with leadership and operators across business units to find automation targets and ship agentic solutions.
Build and maintain integrations across the existing stack, including Microsoft Graph, Entra, SharePoint, Teams, Procore, Azure Functions, Make.com, and third-party APIs.
Create evaluation pipelines and observability for production agents, including cost monitoring, quality tracking, failure-mode detection, and regression testing.
Implement secure agent identity and authorization using managed identities, service principals, OAuth2 flows, least-privilege Graph permissions, and audit logging.
Establish and uphold AI governance standards across entities, covering data handling, model selection, prompt management, version control, and rollback procedures.
Document architectures and key decisions so systems remain maintainable beyond individual engagements.
Stay current with the agentic AI landscape (examples include Claude, OpenAI, Azure AI Foundry, Copilot Studio, LangGraph, MCP) and recommend pragmatic platform approaches.

Requirements

3–5 years of professional software engineering experience, including at least 1 year shipping production AI/LLM systems (not prototypes or demos).
Strong proficiency in Python and/or TypeScript.
Hands-on experience with at least one major agent framework or SDK, such as Anthropic Claude SDK, OpenAI Agents SDK, LangGraph, Vercel AI SDK, Semantic Kernel, or Azure AI Foundry.
Real experience building and interpreting eval harnesses to measure whether an agent is working.
Working knowledge of the Microsoft cloud stack, including Azure Functions, Microsoft Graph API, Entra ID app registrations, OAuth2, and managed identities.
Backend and integration engineering experience with REST APIs, webhooks, queues, state management, and authentication patterns.
Strong written communication skills and the ability to explain trade-offs to a technical leader making investment decisions.
Comfort working onsite in Kennesaw, GA.

Technologies

Microsoft 365, Entra ID, Intune, Azure Functions, Table Storage
Entra Domain Services, Procore, Make.com, Microsoft Graph
Python, TypeScript
Anthropic Claude SDK, OpenAI Agents SDK, LangGraph, Vercel AI SDK, Semantic Kernel, Azure AI Foundry
Microsoft Copilot Studio, Power Automate, Model Context Protocol (MCP), SharePoint, Teams
OAuth2, REST APIs, webhooks, queues, managed identities, service principals
Bicep, Terraform, GitHub Actions, Azure DevOps pipelines

Benefits

Competitive base salary commensurate with experience, plus a full benefits package including health, dental, vision, retirement, and paid time off.
Ongoing learning budgets, conference attendance, and dedicated time for skill development.

What You Bring

Strongly Preferred: Production experience with Microsoft Copilot Studio, Power Automate, or Azure AI Foundry.
Strongly Preferred: Experience with Model Context Protocol (MCP) servers or comparable tool-server architectures.
Strongly Preferred: Familiarity with retrieval-augmented generation (RAG) over enterprise document stores including SharePoint, OneDrive, and Confluence.
Strongly Preferred: Experience working in a multi-entity or multi-tenant environment with cross-cutting identity and data concerns.
Strongly Preferred: DevOps/IaC exposure including Bicep, Terraform, GitHub Actions, or Azure DevOps pipelines.
Strongly Preferred: Familiarity with construction-tech (Procore, Bluebeam) or verticalized SaaS integrations.
Nice to Have: Cybersecurity or compliance background, particularly around AI governance, data classification, or zero-trust principles.
Nice to Have: Open-source contributions to agent frameworks or developer tools.
Nice to Have: Prior experience as the first or second AI hire at an organization.

How You’ll Be Measured

Time-to-production for new agents and automations.
Measurable business impact including hours saved, cycle time reduced, error rates lowered, and revenue accelerated.
System reliability including uptime, eval pass rates, cost efficiency, and incident response.
Quality of the engineering foundation including maintainability, documentation, security posture, and knowledge transfer.

How to Apply

Send a resume and a short note describing one agentic AI system you shipped to production.
Cover letters are not required; the project description is.
Links to public repos, write-ups, or recorded demos are strongly encouraged.

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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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OAuth Data Jobs

Senior Manager, AI Engineer Intelligence Layer

Senior Manager, AI Engineer Intelligence Layer

Agentic AI Engineer

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

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