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# Architect IAM for AI / Platform (PAM-Focused)

- **Company:** TekWissen LLC
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Salary:** $100,000.0 - $120,000.0
- **Contract:** Temporary contract
- **Skills:** Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Cloud Computing, Linux, Distributed Systems, Memory Management, Perl (Programming Language), Identity and Access Management, Python (Programming Language), Kerberos (Protocol), Open Source Technology, Data Logging, Large Language Models, Multi-Agent Systems, Prompt Engineering, Machine Learning Operations, GPT, Data Pipelines
- **Published:** August 21, 2026
- **Apply:** https://www.careerjet.com/jobad/us02e4e17b49b971416de684897d02b200

## About the Role

Proficiency witth:

 * Cprogramming 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), * 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

## Description

* 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


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