Responsibilities
- Work directly with clients and our internal delivery teams to build and deploy AI-powered solutions that transform how work gets done.
- Own projects end-to-end: scoping ambiguous problems, prototyping AI workflows, and deploying scalable systems on top of our products — all while interfacing with technical and non-technical stakeholders.
- Collaborate with delivery leaders to scope technical solutions to operational problems.
- Identify workflow optimizations through deep engagement with customer problems and work to build into a stable and scalable solution.
- Design and implement AI-powered workflows using LLMs, embedding models, retrieval systems, and automation tools.
- Translate messy real-world constraints (e.g., inconsistent data, latency requirements) into elegant engineering solutions.
- Iterate quickly based on real-time feedback from operators and clients.
- Build reusable tooling and infrastructure that accelerates future deployments.
Requirements
- 6+ years of software engineering experience, including significant time spent building data, ML, or backend systems.
- Deep proficiency in Python with hands-on experience using Hugging Face, LangChain, OpenAI, Pinecone, and related ecosystems.
- Skilled in full-stack and API-based deployment patterns, including Docker, FastAPI, Kubernetes, and cloud environments (GCP, AWS).
- Experienced with workflow orchestration libraries, pub/sub systems (Kafka), and schema governance.
- Expertise in data governance and operations, including Unity Catalog and policy management, cluster/job orchestration, data contracts and quality enforcement, Delta/ETL pipelines, and replay processes.
- Strong product and distributed systems skills — you understand business needs and how to translate them into technical architecture.
- Experience building usable systems from messy data and ambiguous requirements.
- Excellent communication and client-facing skills; you’ve led conversations with technical and non-technical stakeholders alike.
- Proven experience owning projects from scoping through deployment in ambiguous, high-stakes environments.
- Strong engineering background demonstrated by a Bachelor’s degree in Data Science, Computer Science and related fields OR equivalent professional experience.
Additional Information
- Be willing to be on-call for our customers when situations arise.
