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

Work you'll do

• 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:

• Ability to work independently and collaborate as part of a team
• Effective written and verbal communication skills
• Meticulous attention to detail and quality of work product
• Ability to build and sustain professional relationships
• Ability to lead projects or work streams
• Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
• Strong interpersonal skills and professional demeanor
• Ability to meet deadlines
• Ability to provide clear guidance to others

Required:

• Bachelor's degree in Cybersecurity, Computer Science, Information Systems, Engineering, or a similar technical field
• Ability to work onsite up to 5 days a 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 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, Git Hub 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)
• Ability to travel 15%, on average, based on the work you do and the clients and industries/sectors you serve.
• 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.
• Delivery Center Location & Travel Requirements:
  • 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)
  • 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
  • Travel Requirement:
    Maximum of 10% overnight travel for client or project purposes
  • Relocation Requirement:
    If relocation is necessary, complete the move within 12 weeks from the start date to reside within a commutable distance

Preferred:

• Experience deploying generative AI solutions to production environments
• Hands‑on experience with identity and access management platforms such as SailPoint, Okta, or Microsoft Entra
• Experience securing non‑human or machine identities, service accounts, secrets, and credentials using tools such as Hashi Corp Vault or Cyber Ark
• Experience with AI agent frameworks and protocols such as Lang Chain, Lang Graph, 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)
• 2+ years of 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