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AI Engineer

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Description

We are looking for an AI Engineer with 3-4 years of software development experience, including hands-on work building applications on Large Language Models (LLMs). The role focuses on building AI agents and LLM-powered features, the harnesses that run and test them, and the monitoring that shows how they perform in production.


The engineer will work with US-based architects and our product and delivery teams to take AI features from prototype to production.


Key Responsibilities:

  • Build AI agents that plan tasks, call tools and APIs, and work with business data.
  • Build and maintain agent harnesses: tool definitions, context and memory handling, guardrails, retries and test runs.
  • Integrate LLMs (OpenAI, Anthropic, Azure OpenAI or open-source models) into applications through their APIs.
  • Build retrieval-augmented generation (RAG) features using vector databases.
  • Write and refine prompts, and build evaluation sets to measure output quality.
  • Add monitoring to AI features: logs, traces and metrics for response quality, latency, errors and token cost.
  • Deploy and support AI services in production on Azure or AWS.
  • Keep up with new models, frameworks and tools, and try them out on real use cases.


Required Qualifications & Skills:

  • Bachelor's or Master's degree in Computer Science, Engineering or a related field.
  • 3-4 years of software development experience, with at least 1-2 years building LLM-based applications.
  • Strong Python, including building REST APIs (for example, FastAPI or Flask).
  • Hands-on experience with LLM APIs, prompt engineering and RAG.
  • Experience with at least one agent framework or SDK, such as LangGraph, LangChain, LlamaIndex, OpenAI Agents SDK or Claude Agent SDK.
  • Working knowledge of monitoring and telemetry: structured logging, tracing and metrics (for example, OpenTelemetry, Langfuse or LangSmith).
  • Familiarity with SQL, Git, Docker and Azure or AWS.


Good to Have:

  • Experience with Model Context Protocol (MCP) servers or multi-agent setups.
  • Experience with document processing or data extraction using LLMs.

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