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# Forward Deployed AI Engineer

- **Company:** Turing Technology, Inc.
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Salary:** $200,000.0 - $250,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Cloud Computing, Databases, Distributed Systems, Python (Programming Language), Software Systems, Systems Integration, Large Language Models, Multi-Agent Systems, Backend, Low Latency, Virtual Agents, Data Pipelines
- **Published:** September 19, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=6928ed888d2144e3

## About the Role

Deep production engineering experience: Typically 8+ years building and operating sophisticated software systems, with expertise in Python, backend systems, APIs, databases, distributed systems, system design, and cloud infrastructure.

Hands-on agentic AI experience: Experience building production LLM and agent systems using orchestration, tool use, context engineering, memory and state, retrieval, and multistep workflows.

End-to-end systems ownership: A track record of taking complex systems from architecture through deployment and scale, with a practical understanding of evaluation, observability, reliability, security, guardrails, latency, scalability, and cost.

Exceptional customer and technical leadership: The ability to enter unfamiliar environments, earn trust quickly, navigate ambiguity, challenge assumptions constructively, and communicate effectively with senior engineers and business executives.

Client-ready communication: The ability to explain technical concepts clearly, navigate ambiguity, work with stakeholders, and remain calm under pressure.

## Description

Work directly with customers to navigate ambiguity, uncover high-value opportunities, challenge assumptions, and translate complex business needs into clear technical direction. This requires curiosity and business acumen as you discover business workflows and jointly define the outcomes an AI solution should drive., Architect and build production AI systems, from multi-agent workflows, orchestration, tool use, context engineering, memory and state, and retrieval-augmented generation (RAG) to the APIs, data pipelines, integrations, and distributed systems that make them reliable at scale.


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