Urgent Need IAM Architect for AI / Platform (PAM-Focused) at NYC (Hybrid)

Hi, 

Pleasure mailing you. Please go through the below requirement and let me know if you are comfortable with the position.

Please send me your updated resume along with the best hourly rate, work authorization status and availability.

An early response is really appreciated.

 

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

Location: NYC (Hybrid)

Duration: 11 months

 

Job Summary:

Overview

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

 

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 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

 

Key Technologies / Areas

• LLM frameworks and orchestration
• Cloud platforms and APIs
• Distributed systems design
• AI governance frameworks

 

 

 

 

	Thanks & Regards Thahura MD US IT Recruiter thahuram@tekskillsinc.com
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