Highlights
Design and implement agent orchestration architectures, including task decomposition, multi agent coordination, tool/function invocation, state and memory management, and policy aware execution flows. Experience translating advanced AI (LLMs, agentic workflows, orchestration) into secure, governed, and auditable capabilities that are production ready for large, regulated enterprises.
Numbers & Facts
| Location | New York, NY |
| Industry | Computer/IT Services |
| Salary | $44–$45.71 |
| Company Size | 100 to 499 employees |
| Year Founded | 2009 |
| Website | http://www.tekwissen.com/ |
Description
Overview:
TekWissen is a global workforce management provider headquartered in Ann Arbor, Michigan that offers strategic talent solutions to our clients world-wide. Our client is a global professional services firm specializing in digital transformation, business process management (BPM), analytics, and AI-driven solutions. The company partners with organizations to improve efficiency, transform operations, and drive business outcomes through a combination of process expertise, technology, and data insight.
TekWissen is a global workforce management provider headquartered in Ann Arbor, Michigan that offers strategic talent solutions to our clients world-wide. Our client is a global professional services firm specializing in digital transformation, business process management (BPM), analytics, and AI-driven solutions. The company partners with organizations to improve efficiency, transform operations, and drive business outcomes through a combination of process expertise, technology, and data insight.
Job Title: PAM Engineer AI
Location: New York, NY
Duration: 11 Months
Job Type: Temporary Assignment
Work Type: Hybrid
Job Description:
Location: New York, NY
Duration: 11 Months
Job Type: Temporary Assignment
Work Type: Hybrid
Job Description:
Job Summary:
- 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.
Required Skills:
- 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.
Preferred Qualifications:
- 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.
TekWissen Group is an equal opportunity employer supporting workforce diversity.
About Company
WE THE TEKWISSEN PEOPLE
TekWissen offers you a broader portfolio of services, industry-leading solutions, and the meaningful innovations that give you greater flexibility and speed to respond to market dynamics, reduced costs and risk to improve enterprise performance, and increased productivity to enable growth.
To keep pace with global market demands, TekWissen keeps its finger on the pulse of change. Our organized approach to guiding a project from its inception to closure. Managing projects is becoming more and more important as we enter the digital era. To cope with the pace that this transition demands, a method is required to manage projects so they can yield quality work, while incorporating efficient use of time and resources.
Project involves identifying which quality standards are relevant to the project and determining how to satisfy them.
It is important to perform quality planning during the Planning Process and should be done alongside the other project planning processes because changes in the quality will likely require changes in the other planning processes, or the desired product quality may require a detailed risk analysis of an identified problem. It is important to remember that quality should be planned, designed, then built in, not added on after the fact.
Capabilities and accomplishments in one TekWissen business enhance the opportunity for success in the others. Put simply, TekWissen's unique combination of attributes promotes success.