Forward Deployed AI Engineer

Turing • Los Angeles, CA

6d • 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 area and focuses on building and deploying production generative AI systems for large enterprises. The engineer owns outcomes end to end, from identifying valuable customer problems and shaping technical architecture through implementation, deployment, and measuring business impact and return on investment.

The role combines customer-facing discovery and technical leadership with hands-on engineering. The engineer will work with clients to understand business workflows, navigate ambiguity, challenge assumptions, and define the outcomes AI solutions should achieve. They will architect and build systems involving multi-agent workflows, orchestration, tool use, context engineering, memory and state, retrieval-augmented generation, APIs, data pipelines, integrations, and distributed systems.

The engineer remains responsible for the quality and operation of deployed systems, including evaluation, observability, security, reliability, latency, scalability, and cost. The position is described as high-ownership and demanding, with client-first work that may require in-person collaboration at client sites. Employees should expect to work in person three to five days per week, depending on assignment and client requirements, and be based in or reasonably close to Los Angeles. As part of an early team in a rapidly scaling startup-like business unit, the engineer will also help develop processes and playbooks.

Turing describes its mission as accelerating superintelligence to drive economic progress. It works with frontier AI labs on datasets, reinforcement learning environments, and research benchmarks, and with large enterprises on end-to-end agentic AI systems. Turing highlights client-first work, startup speed, and an AI-forward approach among its values.

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, business executives, and other stakeholders, including explaining technical concepts clearly.
• Ability to remain calm under pressure and work in a demanding, high-accountability environment.
• Ability to work in person three to five days per week depending on client requirements and be based in the Los Angeles area or within a reasonable commuting distance.

Responsibilities

• Work directly with customers to identify high-value opportunities, understand business workflows, and translate complex needs into technical direction.
• Jointly define the business outcomes an AI solution should drive.
• Architect and build production AI systems, including agent workflows, orchestration, tool use, context engineering, memory and state, and retrieval-augmented generation.
• Build the APIs, data pipelines, integrations, and distributed systems needed to operate AI solutions reliably at scale.
• Lead solutions from discovery through deployment and measurable impact.
• Own evaluation, observability, security, reliability, latency, scalability, and cost for deployed systems.
• Work with senior client leaders and stakeholders, communicate technical concepts clearly, and navigate ambiguous situations.
• Help create processes and playbooks for the Enterprise AI business unit.

Benefits

• Equity.
• Opportunity to work on frontier AI and contribute to datasets, reinforcement learning environments, and research benchmarks.
• Opportunity to contribute to leading-edge AI research and showcase work at conferences such as ICLR, ICML, and NeurIPS.
• Collaboration with colleagues with AI experience from Google, Meta, Amazon, and other leading technology companies.
• Opportunity to apply frontier AI innovations to enterprise business challenges.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed