Senior Machine Learning Engineer, Agentic Systems

Role overview A senior engineering role focused on building and shipping agentic AI systems for mission-critical, real-world deployments. The position sits at the intersection of applied machine learning, software engineering, and platform development, contributing to both customer projects and an internal AI operations product. The work centers on orchestrating LLM-powered agents, integrating them with external tools and data sources, and ensuring reliability once systems leave the lab.

Responsibilities - Design, build, and evaluate LLM-powered agents and multi-step agentic workflows for production use - Develop evaluation frameworks that measure agent performance, reliability, and safety - Integrate AI systems with external tools, APIs, MCP servers, and enterprise data sources - Orchestrate data and agent pipelines that power a proprietary AI operations platform - Analyze deployed systems, surface drift and degradation, and feed improvements back into the product - Collaborate with customers, data scientists, and DevOps engineers on fielded deployments

Requirements - BS in computer science, machine learning, or a related discipline with 6+ years of relevant experience - Demonstrated experience delivering data-centric systems, including ETL pipelines, data cleaning, and production analytics - Hands-on experience building and optimizing LLM agents, RAG, tool use, planning, and multi-agent architectures - Strong Python plus familiarity with TensorFlow, PyTorch, and/or scikit-learn - Solid software engineering fundamentals plus proficiency in at least one systems language (Go, Rust, C++, Java, or Scala) - Proficiency with Agile, version control, CI/CD, issue tracking, and debugging; US citizenship with ability to obtain a Secret clearance

Nice to have - Advanced degree in a related field - Client-server architecture experience (REST, GraphQL, React/Vue/Angular) - Containerized or cloud deployments using Docker, Kubernetes, infrastructure as code - Experience with unstructured data types such as imagery, video, audio, or telemetry - Background leading small teams or delivering in secure government environments

Benefits and work setup Fully remote or hybrid at a northwest Austin, TX office, with up to 20% travel. Anticipated base pay of $160,000–$200,000 plus equity and cash bonuses. Benefits include medical/dental/vision, voluntary life and disability coverage, HSA/FSA, 401(k), unlimited PTO, and paid parental leave.