Forward Deployed AI Engineer

Turing•Los Angeles, CA

2d•Onsite

About The Position

Turing is hiring a Forward-Deployed AI Engineer for its Enterprise AI business unit. The role is based in the Los Angeles Metro area and is in-office three to five days per week, depending on client requirements. The engineer will own client outcomes end to end, from identifying high-value business problems and shaping technical architecture through building, deploying, and evaluating production AI systems. The role involves working directly with customers and senior client leaders to translate complex business needs into technical direction and deliver measurable impact and return on investment. The engineer will architect and build production AI systems, including multi-agent workflows, orchestration, tool use, context engineering, memory and state, retrieval-augmented generation, APIs, data pipelines, integrations, and distributed systems. They will remain hands-on while owning evaluation, observability, security, reliability, latency, scalability, and cost. This is a high-ownership, demanding role in a rapidly scaling startup-style business unit, where the engineer may also help establish processes and playbooks. Turing works with frontier AI labs and Fortune 500 enterprises to develop AI datasets, reinforcement learning environments, research benchmarks, and end-to-end agentic AI systems for mission-critical workflows. The company describes its values as client first, working at start-up speed, and being AI forward. It is an equal opportunity employer and encourages candidates to apply even if their experience does not align with every qualification.

Requirements

Typically 8+ years of experience building and operating sophisticated production software systems.
Expertise in Python, backend systems, APIs, databases, distributed systems, system design, and cloud infrastructure.
Experience building production LLM and agent systems using orchestration, tool use, context engineering, memory and state, retrieval, and multistep workflows.
Track record of taking complex systems from architecture through deployment and scale.
Practical understanding of evaluation, observability, reliability, security, guardrails, latency, scalability, and cost.
Ability to enter unfamiliar environments, earn trust quickly, navigate ambiguity, and constructively challenge assumptions.
Ability to communicate effectively with senior engineers and business executives, explain technical concepts clearly, work with stakeholders, and remain calm under pressure.
Ability to work in person three to five days per week, depending on assignment and client needs, and be based in the Los Angeles Metro area or within a reasonable commuting distance.

Responsibilities

Work directly with customers to navigate ambiguity, uncover high-value opportunities, challenge assumptions, and translate business needs into technical direction.
Discover customer workflows and jointly define the outcomes an AI solution should achieve.
Architect and build production AI systems, including multi-agent workflows, orchestration, tool use, context engineering, memory and state, retrieval-augmented generation, APIs, data pipelines, integrations, and distributed systems.
Lead client solutions from discovery through deployment and measurable impact.
Own evaluation, observability, security, reliability, latency, scalability, and cost while building and operating systems.
Work directly with senior client leaders and communicate technical concepts to engineering and business stakeholders.
Help create processes and playbooks for the Enterprise AI business unit.