What You'll Own
Own the full product loop end-to-end: customer signal → product call → build → deploy → trace → repeat.
Build and maintain full-stack applications using React, Next.js, and Python, with agentic workflows integrated throughout.
Work directly with B2B freight brokerage customers to triangulate between what they say, what they mean, and what they actually need.
Design and implement agentic workflows using tools like Pipecat, LangChain, or equivalent, embedding agents into product surfaces.
Instrument production traces for multiple audiences: engineers debugging, product correctness verification, and customer trust.
Apply strong product judgment to distinguish one-off customer signal from real roadmap direction.
Must-Have
Ship production code daily in Python and TypeScript/React, with real ownership of full-stack systems end-to-end.
Deep understanding of LLM architecture and how to work with foundation models in production, not just prompting.
Strong fundamentals in system design, streaming architecture, and SQL databases.
Comfortable shipping ambiguous, high-stakes decisions with limited data; extreme ownership over your scope.
Hands-on experience with generative AI tooling (Claude Code, Codex) as daily tools, not toys.
Nice-to-Have
Functional programming languages (OCaml, Haskell, Scala, Rust) signal strong programming fundamentals and depth.
VHDL, SystemVerilog, or other hardware-description languages show range and understanding of systems at scale.
Prior founding engineer or early-stage startup experience; evidence of operating without a playbook.
Open-source contributions or personal projects shipping at scale; competitive programming (ICPC) as a supplement to other signals.
Background in building complex orchestration systems, multi-agent coordination, or voice/real-time systems.
Salary :
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