Gen AI Engineer

Gen AI Engineer

Remote | United States | Contract | Competitive Rate

You must hold full working rights in the United States. We're unable to sponsor visas for this role.

About the role

We're looking for a AI Engineer to work alongside our AI Solutions Lead, building production AI applications directly for our client. You'll partner with the client to understand their operational problems, then design and ship full-stack solutions powered by LLMs and agentic workflows. This isn't a back-office build role. You'll own projects from discovery through deployment, working closely with the client team and iterating fast as requirements shift.

What you will do

• Work directly with our client to scope problems and turn them into technical solutions
• Build and deploy production-ready applications with modern full-stack tooling
• Develop LLM features, AI agents, and intelligent workflows inside customer environments
• Build backend services and frontend experiences that hold up under real use
• Run prompt engineering and evaluation cycles to keep improving what's shipped

What you will bring

• Solid background in software engineering or AI engineering, ideally with roots in solutions engineering, implementation, or embedded delivery work before AI made it fashionable
• 8+ years in software engineering overall
• 5+ years in full-stack development (Python and/or TypeScript, React, SQL)
• 2+ years hands-on shipping LLM or generative AI applications in production
• 1+ year working with agent orchestration frameworks (LangChain, LangGraph, or CrewAI)
• 1+ year designing RAG pipelines and working with vector databases
• Comfortable translating business needs into technical decisions with minimal hand-holding
• Genuine interest in where this field is heading, not just the current toolset
• Strong communication skills. You'll be the engineer customers see and trust

Tech skills

Core languages and backend

• Python: non-negotiable for AI orchestration, data scripting, and backend logic
• TypeScript / Node.js: essential for building customer-facing extensions, full-stack glue code, and lightweight web UIs
• SQL and Java/Go: needed for deep database queries and heavy enterprise system extensions
• FastAPI / Flask: for spinning up microservices and rapid integration layers

AI and agent orchestration

• LLM providers: fluency with Anthropic Claude, OpenAI, and open-source models via Hugging Face or vLLM
• Orchestration: production proficiency in LangChain or LangGraph and CrewAI for multi-step agent behaviours
• RAG and vector stores: hands-on design with vector databases (Pinecone, Qdrant, pgvector) and retrieval systems
• Evaluation and observability: deployment tracking using tools like LangSmith or Braintrust to audit hallucination rates and latency

Data and infrastructure

• Databases and warehouses: PostgreSQL, Snowflake, or BigQuery for customer data ingestion
• Cloud platforms: working knowledge of AWS, GCP, or Azure
• Containerisation: Docker as a baseline, with basic Kubernetes and Terraform for replicating environments

Please note, We will ask you to complete a Tech Assessment to be considered for this role.