Staff Product Engineer
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Austin, TX, USA
Posted on Apr 30, 2026
Key Responsibilities
- Own delivery of ML-powered features from concept through production. You are responsible for the feature working in practice.
- Work side by side with our ML experts to drive ideas into reliable, production-ready systems.
- Engage directly with customers and internal stakeholders to understand real-world usage and translate those insights into product and engineering decisions.
- Use AI coding tools (Cursor, Claude Code, or similar) as a primary part of your daily workflow to read, write, and test code, while critically evaluating output and catching subtle errors before they ship.
- Ensure models, retrieval systems, and agent workflows function correctly together across the full system.
- Lead implementation of ML-driven features, coordinating with ML engineers and the rest of the team to get features shipped.
- Build and maintain evaluation systems, including datasets, scoring approaches, and repeatable testing to detect regressions.
- Design and iterate on prompts and agent instructions to ensure correct and predictable system behavior.
- Establish and improve observability, debugging, and testing practices for ML systems.
- Improve the structure, reliability, and maintainability of the ML codebase while preserving development speed.
- Work primarily in Python, and contribute in Go and other languages where needed.
- Modify and work with pipelines, retrieval systems, and model behavior when required.
- Advocate for the right technical approach and push back when needed to keep the work grounded in customer outcomes.
- Orchestrate workflows across APIs, external systems, and multiple data sources.
- Balance rapid experimentation with longer-term system quality.
- Work with customers and internal stakeholders to ensure solutions align with real-world usage.
Experience
- Strong software engineering background, with experience building and owning production systems end to end.
- Strong proficiency in Python and Go, with a track record of building well-structured and maintainable systems.
- Daily, fluent use of AI coding tools (Cursor, Claude Code, or similar) as a core part of your engineering workflow. You write effective prompts, iterate when output is wrong, and reliably distinguish working code from code that only looks right.
- Experience delivering complex features in production environments, ideally involving ML or AI systems.
- Demonstrated ability to take ownership of ambiguous problems and drive them to working solutions.
- Hands-on experience building with LLMs, RAG systems, and agent-based workflows, with a solid conceptual grounding in how these systems work, fail, and need to be evaluated.
- Experience working with LLMs, RAG systems, or agent-based workflows.
- Experience integrating multiple systems, APIs, and data sources into cohesive product functionality.
- Experience designing or working with evaluation systems for ML quality.
- Experience debugging production systems, including handling edge cases and failure modes.
- Experience with observability and debugging in ML or backend systems.
- Experience working with pipelines, retrieval systems, or model behavior such as ranking, fine-tuning, or prompt tuning.
- Comfortable operating in fast-moving environments with high ownership.
- Experience working with customers or customer-facing systems, incorporating feedback into what gets built.
- Familiarity with frontend or full-stack development.
- Experience with MLOps systems, data pipelines, or production ML infrastructure.
- Familiarity with open source models such as LLaMA, Qwen, DeepSeek, Kimi, or similar.
Human Skills
- Ownership mindset with a focus on delivering working systems in production.
- Strong product judgment, with an understanding of how system behavior impacts user experience and trust.
- Critical evaluation of AI output. You spot hallucinated APIs, incorrect logic, and subtle bugs in generated code before they reach production.
- Bias toward action, with a focus on learning through building and iteration.
- Ability to operate effectively in ambiguous environments.
- Systems thinking, including attention to correctness and failure modes.
- Curiosity about how systems behave in practice and how customers use them.
- Low ego, with a focus on team outcomes.
What We Offer
- Early-Stage Ownership: Join at the ground floor of a company with real traction and momentum.
- Empowered Culture: We value autonomy, candor, and craft. You'll be trusted to lead.
- Cutting-Edge Tech: Work with the latest in AI, backend systems, and intelligent infrastructure.
- Meaningful Impact: Shape a platform that transforms how organizations activate knowledge.
- Holistic Benefits: Competitive comp, equity, 100% paid healthcare, 401K, flexible PTO, and a team that truly cares.
This job is no longer accepting applications
See open jobs at Circuit.See open jobs similar to "Staff Product Engineer" Capital Factory.