Forward Deployed Engineer Trida AI New York, NY (Remote) Contract · 1 week ago

Trida Labs; New York (NY); Remote; USD 138,000 - 207,000; Part time

Job summary

Trida AI deploys Forward Deployed Engineers inside enterprise customer teams to design, build, and ship production AI systems — agents, retrieval, and data integrations — and to leave behind systems the customer can operate themselves. Success is production adoption and measurable workflow impact, not a demo.

Travel to customer sites up to 50% may be required depending on the engagement. What You'll Do: Own deployment end-to-end; embed with customer teams; design and ship LLM agents, retrieval

Qualifications

• 4–6 years of engineering experience, including customer-facing work.
• Experience building and deploying LLM-powered systems in production — RAG, agentic workflows, tool use / MCP.
• Strong written and spoken communication and ability to work with VP-level stakeholders.

Responsibilities

• Own deployment end-to-end: discovery, scoping, design, build, evaluation, rollout, handoff.
• Embed with customer teams and build inside their systems.
• Design and ship LLM agents, RAG pipelines, and data integrations with enterprise APIs.
• Define acceptance criteria and launch readiness evaluations.
• Codify learnings into repeatable patterns, playbooks, and building blocks for future engagements.
• Provide feedback to delivery leadership.

Skills

LLM production systems

RAG pipelines

Agentic workflows

Python

Tools

LLM Orchestration

MCP Servers

APIs integration

Job description

Applications may be assessed in part using Trida's skill-based tools (verified certifications, skill tests, and FitScore), always alongside human review before any hiring decision.

Location: New York, New York, United States

Work Model: Remote

Employment Type: Contract

Experience: 4–6 Years

Compensation: $100–$150 per hour

About Trida AI

Trida AI is a Forward Deployed Engineering services company that helps enterprises design, build, and deploy production AI systems. Our engineers embed with customer teams to ship agentic workflows, retrieval and data integrations, and the evaluation and hardening work that turns pilots into dependable production systems. Trida AI is expanding its services footprint across the United States as demand for production AI delivery grows.

About the Role

Trida AI deploys Forward Deployed Engineers inside enterprise customer teams to design, build, and ship production AI systems — agents, retrieval, and data integrations — and to leave behind systems the customer can operate themselves. Success is production adoption and measurable workflow impact, not a demo. Travel to customer sites up to 50% may be required depending on the engagement.

What You'll Do

• Own a customer deployment end to end: discovery, technical scoping, system design, build, evaluation, production rollout, and handoff
• Embed with customer engineering and domain teams and build inside their systems
• Design and ship LLM agents, retrieval (RAG) pipelines, and integrations with enterprise data and APIs
• Define acceptance criteria and evaluations that gate launch readiness
• Codify what you learn into repeatable patterns, playbooks, and building blocks for the next engagement
• Feed field insights back to Trida AI delivery leadership

What We're Looking For

• 4–6 years of engineering experience, including customer-facing work
• You have built and deployed LLM-powered systems in production — RAG, agentic workflows, tool use / MCP
• High agency in ambiguity; you can work with engineers and VP-level stakeholders in the same day
• Strong written and spoken communication

Additional Information

Trida AI LLC is an equal opportunity employer. We welcome applicants of all backgrounds. If you need an accommodation in the application process, contact [e-mail].

Location: Remote — United States (New York, NY base). Skills: Forward Deployed Engineering, Agentic Workflows, RAG, LLM Orchestration, MCP Servers, Python.

About Trida AI

Forward-deployed AI engineers embedded in your company to build, ship, and run AI systems that actually work in production.