- Company Name
- Aurora
- Job Title
- Founding Product Engineer (AI & Agentic Systems)
- Job Description
-
Job Title: Founding Product Engineer (AI & Agentic Systems)
Role Summary:
Lead end‑to‑end development of AI‑driven user features, acting as both product owner and senior engineer. Own problem definition, design, implementation, launch, and iteration of AI workflows, ensuring alignment with customer value and operational reliability.
Expectations:
- Deliver production‑ready AI features at scale within an agile team.
- Translate ambiguous concepts into concrete, deployable systems.
- Balance technical feasibility, latency, cost, and user experience.
- Influence product direction through data‑driven insights and metrics.
Key Responsibilities:
- Own feature life cycle: research, scope, design, build, test, release, and iterate.
- Design AI workflows using LLMs, tool calling, and agentic flows.
- Implement ML features (classification, ranking, extraction, decision support).
- Build data pipelines, embeddings, retrieval, and RAG components.
- Collaborate with backend, mobile, and operations teams for scalable deployments.
- Define success metrics, monitor performance, and incorporate qualitative and quantitative feedback.
- Diagnose and resolve production issues related to AI behavior, data quality, or workflow logic.
- Contribute code across the stack with a focus on shipping value.
Required Skills:
- 4+ years building production software.
- Proven experience shipping AI/ML features at scale.
- Expertise with LLMs, prompt engineering, tool calling, and agentic systems.
- Strong Python programming, API design, and backend integration.
- Knowledge of data pipelines, embeddings, retrieval, and RAG architectures.
- Understanding of ML system failure modes, latency, cost, and reliability trade‑offs.
- Product‑oriented mindset: define problems, prioritize user outcomes, iterate quickly.
- Excellent communication and collaboration across engineering, product, and operations.
Required Education & Certifications:
- Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent experience).
- Certifications in ML/AI or relevant technical domains preferred but not mandatory.