GenAI Engineer – Java Backend
What you will do:
- Build agentic features, hands-on. Work alongside senior engineers to design and ship AI-powered remediation capabilities: agent workflows, retrieval pipelines, evaluation loops.
- Write production code daily. Java/Spring Boot microservices and AI integrations on AWS.
- Learn the full lifecycle. From an idea in a design doc to something running in production, instrumented, monitored, and improved based on real usage.
- Bring fresh eyes. You're closer to the newest models, frameworks, and techniques than engineers who've been heads-down in one stack for a decade — we want that perspective in the room, not just deference to seniority.
- Grow fast. Work directly with senior engineers who'll push your technical depth, and take on more ownership as you earn it. Our stack
- Java / Spring Boot microservices on AWS (Lambda, SQS, SNS, IAM, CloudWatch). AI stack: AWS Bedrock and AgentCore, MCP for tool integration, RAG pipelines with vector and graph-based retrieval, LLM-as-judge evaluation. Some Python and Go at the edges. You won't know all of this — we're more interested in how fast you pick things up than what's already on your resume.
What you will bring:
- 4+ years building software professionally — you've shipped real features, not just coursework or side projects, and you understand what "production" demands.
- Genuine curiosity about AI/agentic systems — you've built something with LLMs or agents, even outside of work: a side project, a hackathon entry, an experiment that didn't ship. We want to hear about it.
- Solid engineering fundamentals — distributed systems basics, APIs, cloud infrastructure (AWS). You need to know what good code and good design look like.
- You experiment and iterate ideas quickly and bring new perspectives
Nice to have:
- Experience with multiple LLM APIs or agent frameworks
- Python or Go
- POCs using AI for coding, automation, or data work
- Contributions to open source AI/ML tooling.