Lead Engineer - AI

📋 Description

• Define and own end-to-end AI systems architecture across features and APIs.
• Drive ADRs, design reviews, and RFC processes across squads.
• Set standards for integrating SLM/LLM endpoints into product surfaces.
• Evaluate AI infra patterns (RAG, agentic orchestration, vector stores).
• Own the technical roadmap for AI tooling and model integration.
• Hands-on contributor, delivering critical-path features and shared infra.

🎯 Requirements

• Education: Bachelor’s or Master’s in Computer Science or related field.
• Experience: 6–8 years in software engineering; 2+ years as lead; 8–12 months with AI coding tools; shipped production systems; collaboration with ML teams.
• Technical Skills — Core Engineering: Languages: Python, TypeScript, Go; Architecture: Microservices, REST/GraphQL/gRPC; Databases/Vector: PostgreSQL/MySQL, MongoDB/Redis, FAISS/Pinecone/Weaviate; Cloud/DevOps: AWS/GCP/Azure; Docker, Kubernetes; CI/CD; IaC.
• AI / ML Integration Skills (Mandatory): Proficiency with AI coding assistants (Cursor IDE, Claude Code, Codex CLI); design/consume LLM/SLM inference APIs; RAG/vector stores; AI code quality standards; LLMS limitations awareness.
• Nice to Have: SLM/LLM training pipelines (SFT, RLHF, LoRA); agentic frameworks (LangChain, LlamaIndex, AutoGen, CrewAI); open-source ML contributions; secure coding awareness.
• Behavioural Competencies: AI-First mindset; systems thinking; ownership; influence without authority; clear communication; mentorship; pragmatism; curiosity.

🎁 Benefits

• Partner with internal customers to understand needs.
• Learn what customers need and deliver value.
• Do it. Own it.
• Be fearless accountability in everything.
• Continuously improve and raise standards.
• Build each other up and grow together.