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Architect IAM AI​/Platform; PAM-Focused

Job in New York City, Richmond County, New York, USA
Listing for: Compu-Vision Consulting Inc.
Full Time position
Listed on 2026-07-12
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Software Architect
Job Description & How to Apply Below
Position: Architect IAM for AI / Platform (PAM-Focused)

Job Title:
Architect IAM for AI / Platform (PAM-Focused)

Location: NYC, NYC (3 days onsite minimum)
Duration: 11 months

Look for Local resouces as first priority, or someone who can relocate to NYC

Job Summary:
Overview
Hands-on engineering leadership role focused on AI platforms, LLM systems, and orchestration (with strong IAM/PAM alignment).

Key Skills & Background
Proficiency with:

  • C programming language
  • Unix/Linux systems
  • Knowledge of:
  • Cryptography
  • Authentication & authorization concepts
  • Experience working in:
  • Secured enterprise environments
  • Agile development teams
Engineering Skills
  • Python and Perl development
  • Ability to communicate technical concepts to business stakeholders
  • Strong collaboration and independent execution capabilities
  • Contributions to Linux/Unix/open-source projects are valued
  • Knowledge of Kerberos (preferred)
Core Responsibilities
  • AI / LLM Platform Engineering
  • Lead hands-on development of AI-enabled and LLM-based applications
  • Build agentic and multi-agent systems
  • Design and implement orchestration architectures including:
  • Function invocation
  • State and memory management
  • Policy-aware execution
AI Engineering & Integration
  • Develop intelligent agent workflows using:
  • Prompt design
  • Grounding strategies
  • Tool orchestration layers
Platform Ownership
  • Own full-stack AI system architecture:
  • APIs
  • Data pipelines
  • Model serving and observability
  • Ensure performance, scalability, and reliability across environments
Security & Governance
  • Embed secure-by-design principles, including:
  • Access controls
  • Logging and traceability
  • Explainability
  • Human-in-the-loop safeguards
  • Drive reviews, mentoring, and best practices for AI engineering
Required Skills
  • Hands-on platform engineering experience end-to-end
  • Deep expertise in:
  • LLMs and model lifecycle
  • Prompt engineering and grounding
  • Hallucination mitigation
  • Strong system design experience including:
  • Multi-agent architectures
  • Distributed systems
  • Cloud-native development
Key Technologies / Areas
  • LLM frameworks and orchestration
  • Cloud platforms and APIs
  • Distributed systems design
  • AI governance frameworks
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