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

Job Summary

As organizations adopt generative AI, securing how AI agents, models, and automated workflows access enterprise systems and data has become a core engineering challenge. As an Identity & Gen AI Engineer, you will build generative AI solutions with identity, access, and trust engineered in from the start, securing both human and non-human identities and governing how AI agents and GenAI platforms reach data and downstream systems. This role focuses on hands-on engineering, integration, and continuous enhancement of AI solutions in which identity and access controls are a first-class concern.

Responsibilities

• Build and integrate generative AI solutions, including LLM applications, retrieval-augmented generation, and AI agents, with secure access to data and downstream systems.
• Engineer authentication, authorization, and identity controls for AI agents, service accounts, and other non-human identities operating 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 that 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.

Qualifications

• Bachelor's degree in Cybersecurity, Computer Science, Information Systems, Engineering, or a similar technical field.
• 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 large language model (LLM) applications, retrieval-augmented generation (RAG), or AI agents, including use of model APIs, orchestration frameworks, and AI development tools such as Claude Code, OpenAI Codex, GitHub Copilot, or Cursor.
• Working knowledge of identity and access management concepts and protocols, including authentication, authorization, single sign-on (SSO), and standards such as OpenID Connect (OIDC), Security Assertion Markup Language (SAML), OAuth, and JSON Web Token (JWT).
• Experience deploying generative AI solutions to production environments.
• Experience with identity and access management platforms such as SailPoint, Okta, or Microsoft Entra ID.
• Experience securing non-human or machine identities, service accounts, secrets, and credentials using tools such as HashiCorp Vault or CyberArk.
• Experience with AI agent frameworks and protocols such as LangChain, LangGraph, or Model Context Protocol (MCP).
• Experience with fine-grained authorization or policy-as-code using tools such as Open Policy Agent (OPA), Cedar, or OpenFGA.
• Familiarity with AI and LLM security risks such as the OWASP Top 10 for LLM Applications, prompt injection, and excessive agency.
• Experience applying AI governance and risk frameworks such as the NIST AI Risk Management Framework (AI RMF).
• Experience building or deploying workloads in cloud environments such as Amazon Web Services (AWS) and Microsoft Azure.
• Certified Information Systems Security Professional (CISSP), Certified Cloud Security Professional (CCSP), or a cloud engineering certification such as AWS Certified Solutions Architect or Microsoft Certified: Azure Solutions Architect.
• 1+ year of experience supporting federal government environments.
• 1+ year of experience with infrastructure-as-code or automation technologies such as Terraform or Ansible.