About the Role
We are looking for a GenAI Engineer to build and deliver practical AI and agentic features for client applications. You will implement multi-step agent workflows, connect LLMs with external APIs and databases, and take features from prototype to production. Working alongside international engineering squads, you'll help build production-grade AI applications that go beyond simple API wrappers.
What You Will Do:
- Agent Workflows: Implement stateful agentic workflows, prompt templates, and tool-calling flows using frameworks like LangGraph.
- System & Tool Integration: Connect LLMs and AI agents to internal and external APIs, databases, and third-party tools.
- RAG Implementation: Build and optimize retrieval-augmented generation (RAG) pipelines using vector databases and structured outputs.
- AI Safeguards: Implement standard safeguards for user-facing AI features, including rate limiting, content moderation, and basic guardrails.
- Smart Engineering: Use AI-assisted development tools (e.g., Cursor, GitHub Copilot) to accelerate coding, write unit tests, and troubleshoot complex issues.
- Evals & Quality: Apply prompt evaluation, tracing, and monitoring practices to ensure reliable output from AI components.
- Collaborative Execution: Partner with backend engineers and QA to integrate GenAI components seamlessly into core product architectures.