Full Stack AI Engineer (Senior Level)

Responsibilities

• Design Leadership: Own and lead complex system design discussions, architectural decisions, negotiate and shape builds.
• Feasibility & Scoping: Assess technical feasibility of AI product ideas, produce scoping documents to prevent scope creep.
• Technology & Frameworks: Define tech stacks, build reusable frameworks, establish engineering guidelines.
• Experimentation: Build prototypes, align with stakeholders, evaluate early signals to kill or accelerate.
• Cross-functional Collaboration: Partner with research, operations, data teams; juggle workstreams and tradeoffs.
• Excellence: Build scalable systems, lead AI application evaluation practices.

Qualifications

• Staff-level with 10+ years software engineering experience owning complex systems end-to-end.
• Strong full-stack engineer with extensive AI/ML experience; systems, architecture, tradeoffs focus.
• Design ambiguous problems into reliable, scalable AI harnesses; lead design discussions.
• Production AI systems: agentic workflows, multi-agent orchestration, HITL pipelines, LLM apps, RAG, vector stores, semantic search, multi-model stacks.
• Context engineering for AI limitations.
• Distributed systems in AI/data platforms.
• Agentic coding proficiency to boost output.
• Quick learner across technical domains.

Nice to Have

• Experience at AI data companies (Scale AI, Surge, Snorkel, Labelbox) building synthetic data pipelines, eval environments, task generation.
• Human data labeling interfaces, annotation workflows, data collection pipelines.
• Preference data, reward models (RLHF, RLVR).
• Proficiency: Python, TypeScript, AWS, GCP, Terraform, Temporal Cloud, containerization, LLM gateways, RAG frameworks, data pipeline tooling.