PAM Engineer with AI/ML

Job Title: PAM Engineer with AI/ML

Location: New York or Montreal or Alpharetta, GA (3x a week onsite)

Duration: 6 Months Contract

Key Responsibilities:

• Lead hands-on development of AI enabled and LLM based applications, including agentic and automation?driven systems.
• Design and implement agent orchestration architectures, including task decomposition, multi?agent coordination, tool/function invocation, state and memory management, and policy-aware execution flows.
• Engineer robust LLM interaction layers, including prompt design, grounding strategies (e.g., RAG), tool integration, feedback loops, and evaluation mechanisms.
• Own end-to-end AI system architecture, spanning APIs, services, data pipelines, model serving, and observability.
• Ensure AI solutions operate effectively across cloud-native and hybrid environments, with attention to scalability, latency, and reliability.
• Embed security, compliance, and governance-by-design, including access controls, logging, traceability, explainability, and human?in?the?loop safeguards.
• Provide technical leadership through architecture ownership, hands-on coding, design reviews, and mentorship of AI engineers.

• Proven experience as a hands-on AI or platform engineer with leadership responsibility for production systems.
• Deep expertise in LLMs, including model selection, prompt engineering, grounding techniques, evaluation, and mitigation of hallucination and drift.
• Strong experience with agent frameworks and orchestration patterns, including multi?agent systems, tool?using agents, and agent lifecycle management.
• Solid background in cloud?native architecture, APIs, distributed systems, and modern MLOps/LLMOps practices.
• Ability to translate business, risk, and regulatory requirements into concrete technical designs and implementations.
• Experience translating advanced AI (LLMs, agentic workflows, orchestration) into secure, governed, and auditable capabilities that are production?ready for large, regulated enterprises.
• Experience with real-world deployments scenarios ensuring AI solutions work reliably across hybrid environments, integrate with enterprise platforms, and deliver measurable business outcomes.

• Experience implementing AI control frameworks (e.g., model controls, guardrails, evaluation, and auditability) aligned to NIST, ISO, or sector regulators.
• Knowledge of identity, access, and authorization models for agents and non?human identities, including least?privilege and JIT patterns.
• Familiarity of frameworks such as OWASP Top 10 for Agentic and LLM Applications, MITRE ATLS and NIST AI RMF.