AI Engineer (GCP)

We're looking for a hands-on AI Engineer to join our Innovation team, where the mission is to prove out what's next — fast. You'll spend your time exploring emerging GenAI patterns, graph-driven architectures, and agentic workflows, translating fuzzy ideas into working proofs of concept that inform how the business adopts AI at scale. This is a builder's seat: you'll prototype, iterate, and demo — not maintain legacy pipelines.

What You'll Do

• Design and ship rapid PoCs across GenAI use cases: RAG, agentic workflows, LLM orchestration, semantic search, and knowledge graphs.

• Apply graph theory and graph-based data structures (Neo4j, NetworkX, GraphRAG, LangGraph) to model relationships, enable multi-hop reasoning, and power retrieval systems.

• Build end-to-end AI pipelines integrating LLMs (OpenAI, Anthropic, Azure OpenAI, Hugging Face) with vector stores, embeddings, and enterprise data.

• Write clean, performant SQL to shape training/eval datasets and integrate structured data into GenAI workflows.

• Evaluate emerging tools and frameworks (LangChain, LangGraph, LlamaIndex, MCP, Pinecone, Weaviate, FAISS) and recommend what earns a spot in the stack.

• Partner with product, data science, and business stakeholders to translate ambiguous problems into demoable prototypes within tight sprints.

• Document findings, benchmarks, and trade-offs so successful PoCs can hand off cleanly to production teams

Qualifications:

• 3+ years of engineering experience with at least 1+ years hands-on in AI/ML or GenAI.

• Strong Python; production comfort with LangChain, LangGraph, or equivalent LLM orchestration frameworks.

• Demonstrated experience with Generative AI: RAG, prompt engineering, embeddings, fine-tuning (LoRA/PEFT), agentic systems.

• Working knowledge of graph theory — graph databases, graph algorithms, or GraphRAG-style retrieval.

• Solid SQL and comfort working with structured + unstructured data.

• GCP Cloud experience, including GKE, Big Query, Vertex AI, etc.

Exact compensation may vary based on several factors, including skills, experience, and education.