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.
Work you'll do
As an Identity & Gen AI Engineer on the Identity and Access Management team, you will be responsible for...
- 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.
A successful candidate would possess these skills:
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Ability to work independently and collaborate as part of a team
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Effective written and verbal communication skills
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Meticulous attention to detail and quality of work product
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Ability to build and sustain professional relationships
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Ability to lead projects or workstreams
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Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
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Strong interpersonal skills and professional demeanor
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Ability to meet deadlines
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Ability to provide clear guidance to others
The team
Our Deloitte Cyber team understands the unique challenges and opportunities businesses face in cybersecurity. Join our team to deliver powerful solutions to help our clients navigate the ever-changing threat landscape. Through powerful solutions and managed services that simplify complexity, we enable our clients to operate with resilience, grow with confidence, and proactively manage to secure success.
Our Digital Trust & Privacy offering enables trust and safety of online communications and digital products, protecting users, consumers, and patients from harm. Enables clients to provide consumer confidence in knowing with whom they are dealing and ensuring the integrity of access to data.
This opportunity sits within our Deloitte US Delivery Center model, which is dedicated to driving impactful business services. It leverages Deloitte's scale and talent, as well as a center delivery model to provide high-quality, cost-effective service with standardized processes and procedures to service businesses across Deloitte.
The Deloitte US Delivery Center has a small-business feel with a big-business impact. With the resources of Deloitte and a community feel, the delivery center model provides high-quality services to our clients. USDC professionals work out of one of our specific delivery center locations, and each location presents dynamic career opportunities for professionals to focus on their work with nominal travel requirements.
Qualifications
Required:
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Bachelor's degree in Cybersecurity, Computer Science, Information Systems, Engineering, or a similar technical field
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Ability to work onsite up to 5 days a week.
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3+ years of software engineering experience with Python or a comparable language
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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
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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)
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Ability to travel 15%, on average, based on the work you do and the clients and industries/sectors you serve.
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Ability to obtain and maintain the necessary security clearance.
- Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future.
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Delivery Center Location & Travel Requirements:
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Hybrid Work Model: Operate under a hybrid system requiring residence within a commutable distance to one of the US Delivery Center locations (Gilbert, Lake Mary, or Mechanicsburg) or Geo-Hub locations (Atlanta, Charlotte, Dallas, Houston, and Philadelphia)
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Co-location Expectation: Spend up to 30% of working time co-located at an assigned office for orchestrated opportunities, including projects, practice sessions, training, and Moments That Matter at a Deloitte Delivery Center location, Geo-Hub location, approved site, or project location
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Travel Requirement: Maximum of 10% overnight travel for client or project purposes
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Relocation Requirement: If relocation is necessary, complete the move within 12 weeks from the start date to reside within a commutable distance
Preferred:
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Experience deploying generative AI solutions to production environments
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Hands-on experience with identity and access management platforms such as SailPoint, Okta, or Microsoft Entra ID
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Experience securing non-human or machine identities, service accounts, secrets, and credentials using tools such as HashiCorp Vault or CyberArk
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Experience with AI agent frameworks and protocols such as LangChain, LangGraph, or Model Context Protocol (MCP)
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Experience with fine-grained authorization or policy-as-code using tools such as Open Policy Agent (OPA), Cedar, or OpenFGA
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Familiarity with AI and LLM security risks such as the OWASP Top 10 for LLM Applications, prompt injection, and excessive agency
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Experience applying AI governance and risk frameworks such as the NIST AI Risk Management Framework (AI RMF)
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2+ years of experience building or deploying workloads in cloud environments such as Amazon Web Services (AWS) and Microsoft Azure
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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
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1+ year of experience supporting federal government environments
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1+ year of experience with infrastructure-as-code or automation technologies such as Terraform or Ansible
