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Checked on their board 15 Nov

Trail Hiring now

Forward Deployed Engineer (Contract)

Context layer that helps AI agents make business decisions. You'd build AI features with customers and ship them to production.

Remote (India)ContractPosted 20 days ago
Who to email about itThe Head of Engineering at TrailTheir email address, hidden
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About the role

From Trail's posting on Ashby, as they wrote it

About Us

Trail is the context layer AI agents run on. We're building the missing layer between your company's rules, exceptions, and institutional knowledge and the agents trying to act on them. It's a governed graph that lets any agent or platform, including Trail agents, make the right call on your most complex business processes. Agents today fail not because models are weak, but because they're never given the judgment a business builds up over years. We're fixing that.

Visit our Website and Youtube to learn more!

About the role

In this role, you will work directly with customers to design, build, and deploy AI-driven systems into live production environments. You will operate at the intersection of frontend, backend, and infrastructure, owning problems end-to-end — from initial requirements to production rollout. You will design AI-native interfaces and workflows, integrate LLM-powered systems, and build real-time applications that connect software to physical operations.

Qualifications

● 2+ years as a Forward Deployed Engineer, software engineer, ML engineer or equivalent — startup experience preferred; founder or

founding engineer background is a plus.

● Experience building AI-native applications, including: chatbot /

conversational interfaces, agentic workflows, RAG systems.

● Strong understanding of frontend system design, including: state

management (local vs global vs server state), performance optimization, caching, and rendering patterns.

  • Solid understanding of backend and infrastructure systems, including APIs, data flow, authentication/authorization, and secure data handling — with the ability to debug, design, and collaborate effectively across these layers
  • Hands-on experience building production LLM systems, including RAG pipelines, agent orchestration, embeddings/vector search, and prompt design — with a strong understanding of trade-offs (latency, cost, hallucinations, reliability)
  • Ability to own problems and systems end-to-end, from first principles and problem definition through design, implementation, and production. ● Strong foundations in computer science and software engineering principles
  • Experience working in client-facing or high-ownership environments is a plus

Location : Remote

Live on Trail's board as of 15 Nov. We check it every day.

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