Software Engineer, AI Systems

Role overview A product-focused engineering role on the team building a data intelligence and agentic AI platform for engineering and scientific workloads. The position spans LLM-backed services, agents, retrieval systems, evaluation harnesses, and the data pipelines that move files between customer environments, cloud object storage, and compute clusters. The work is collaborative and product-led: pairing with Product to sharpen specs, owning technical design for a meaningful area, and shipping in small, frequent releases.

Responsibilities - Build and operate production APIs, agents, and retrieval systems that integrate with internal and external services. - Design and run evaluations for agent and RAG workflows, then use the results to drive measurable quality and reliability improvements. - Develop ingestion pipelines and high-throughput data paths that connect customer environments, object storage, and compute clusters while balancing reliability, performance, and cost. - Partner with Product and Design to convert broad goals into well-scoped problems, practical specs, and incremental releases. - Identify worthwhile improvements, pull in the right collaborators, and follow through from decision to launch. - Work primarily in backend services in Python, Java, or Go on AWS, Azure, or GCP with containers and Kubernetes, and contribute occasional UI changes in React and TypeScript.

Requirements - 3–5 years of experience building and operating backend services and distributed systems in at least one major cloud provider (AWS, Azure, or GCP). - Hands-on production experience with agentic AI, retrieval-augmented generation, and evaluations, with the ability to explain how evals led to changes in a shipped system. - Strong proficiency in at least one of Python, Java, or Go, with comfort working across service boundaries and APIs. - Experience with data-intensive infrastructure such as object storage, relational databases, caches, and queues or streaming systems. - Practical use of AI coding agents in day-to-day development, combined with the judgment to verify their output and explore new AI engineering practices. - A BS in Computer Science or equivalent practical experience, plus the ability to turn ambiguous goals into plans, make sound architectural decisions, and own post-launch performance.

Nice to have - Background working on platforms that serve scientific, engineering, or HPC-adjacent customers. - Comfort contributing to React and TypeScript front-ends alongside backend work.

Benefits and work setup - The organization is described as an equal opportunities employer welcoming applicants from all qualified candidates regardless of race, sex, disability, religion/belief, sexual orientation, or age. - Employment is contingent on successful completion of a standard background check. - The team emphasizes a collaborative, inclusive culture that values curiosity, empathy, openness to feedback, and respect for differing perspectives.