Why this role exists:
We are growing our AI team and are looking for a Senior AI / Generative AI Engineer to build and operate production-grade LLM-based systems across the platform.
This role focuses on applied Generative AI: internal AI automation, chatbots, AI assistants, and MCP-based services already used in production. You will work on top of an existing ML and data platform, building systems that are reliable, maintainable, and practical to operate.
This is a hands-on engineering role with end-to-end ownership. Not research. Not prompt-only.
What you’ll drive:
Technical Ownership
— Own LLM-based systems from design to production support. — Design architectures for Generative AI systems (RAG, agents, tool/context serving). — Make clear trade-offs between quality, latency, cost, and complexity. — Set engineering standards for building and operating AI systems in production. — Act as a technical reference point for applied GenAI.
Hands-on AI Engineering
— Build and maintain production LLM-powered systems. — Develop chatbots and AI assistants with predictable behavior. — Design and implement RAG pipelines (ingestion, embeddings, retrieval, generation). — Implement agent-style workflows with tool/function calling. — Build and integrate MCP servers or similar context/tool-serving components. — Integrate AI systems with backend services and ML infrastructure.
Production & Reliability
— Design evaluation frameworks for LLM outputs. — Monitor LLM behavior, system health, and costs in production. — Address performance, scalability, and operational issues. — Handle production incidents and contribute to long-term fixes. — Design systems with failure modes, fallbacks, and graceful degradation.
What makes you a GR8 fit
Must-have
— Strong software engineering background. — Proven experience building LLM-based systems in production. — Hands-on experience with: LLMs and RAG architectures, Chatbots or conversational AI systems, Tool/function calling and agent-style patterns. — Experience with context or tool-serving systems (MCP or similar). — Experience integrating AI into real-time production products. — Understanding of performance, scalability, and cost trade-offs. — Cloud experience (preferably AWS). — Strong engineering fundamentals (testing, debugging, reviews, observability).
Nice-to-have
— Multi-agent or workflow-based systems. — Fine-tuning or adapting open-source LLMs. — ML platforms / MLOps background. — Experience operating latency- or cost-sensitive systems. — Production incident ownership in AI systems.
Tech Stack: Languages: Python, SQL. LLMs: Amazon Bedrock, OpenAI, Anthropic, open-source models. Frameworks: LangChain, LangGraph, Pydantic, Langfuse. RAG: Embeddings, Qdrant / FAISS / OpenSearch / pgvector. Cloud: AWS (ECS / EKS / Lambda, S3, OpenSearch). DevOps: Docker, Git, CI/CD.
Why you’ll love working here:
Benefits Cafeteria — annual budget you allocate to:
Sports • Medical • Mental health • Home office • Languages.
Work-life & support
— Paid maternity/paternity leave + monthly childcare allowance. — 20+ vacation days, unlimited sick leave, emergency time off. — Remote-first + tech support + coworking compensation. — Team events (online/offline/offsite). — Learning culture with internal courses + growth programs.
Our culture & core values:
GR8 Tech culture is how we win — through trust, ownership, and a growth mindset. We move fast, stay curious, and keep it real, with open feedback, room to experiment, and a team that’s got your back.
FUELLED BY TRUST: we’re open, honest, and have each other’s backs.
OWN YOUR GAME: we take initiative and own what we do.
ACCELER8: we move fast, focus smart, and keep it simple.
CHALLENGE ACCEPTED: we grow through challenges and stay curious.
BULLETPROOF: we’re resilient, ready, and always have a plan.
