Senior Member of Technical Staff

ABOUT BLITZY Blitzy is a Cambridge, MA based AI software development platform on a mission to revolutionize the software development life cycle by autonomously building custom software to unlock the next industrial revolution. We’re transforming how enterprises build software, turning enterprise requirements into production-ready code with an agentic software development platform that can autonomously execute 80% of the quantum of software development work. We’re backed by multiple tier 1 investors, and have proven success as founders of previous start-ups. THE ROLE We are hiring a Senior Member of Technical Staff that has two responsibilities that sharpen each other: take Blitzy into territory it hasn't been tested in real, production-grade open source work at the limits of what autonomous development can do and evaluate the engineers we hire to push it further. Everything you encounter building with Blitzy what holds up, what breaks, what's missing goes directly into the product roadmap. This is the most direct feedback loop we have. WHAT YOU’LL OWN PUSHING THE PLATFORM FRONTIER - Select and build production-grade open source projects using Blitzy's autonomous development platform. The work has to be real enough to expose genuine capability limits, prototypes don't count - Document with precision where the platform holds and where it doesn't, specific failure modes, missing capabilities, incorrect assumptions and translate that into product decisions the engineering team can act on - Hold Blitzy to the standard you would apply to any production system: correctness, reliability, operational durability - Ship open source work that demonstrates what autonomous development can actually produce at the frontier TECHNICAL EVALUATION - Assess Principal, Staff, and engineering candidates with the depth that level requires the difference between someone who can reason about a distributed system under failure and someone who has memorized the right things to say about one - Evaluate candidates across the full stack: backend systems, distributed infrastructure, data architecture, LLM/AI systems, and system design under real constraints - Produce structured, specific hiring feedback, the kind that makes the decision obvious, not the kind that defers it - Own the technical bar for engineering hires and evolve it as the platform grows in scope and complexity WHAT SUCCESS LOOKS LIKE - You ship non-trivial open source software with Blitzy and can give a precise account of what autonomous development made possible and where it required you to work around it - The platform feedback you produce drives product changes — not eventually, but because what you surface is specific enough to act on immediately - Your hiring assessments are sought out because they're consistently accurate and the reasoning behind them is traceable - You define your own work, structure it, and execute without requiring direction the output speaks for itself WHAT WE’RE LOOKING FOR - Python as primary language; Node.js and JavaScript as supporting - Microservices architecture; REST and gRPC in production - GCP required; deep hands-on experience in at least one of AWS or Azure - Kubernetes at the level where you've debugged production failures, not just deployed workloads - Terraform; infrastructure as code as a discipline, not a convenience - SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, Cassandra, DynamoDB), chosen for the problem, not defaulted to - Graph databases (Neo4j) for complex relational modeling; vector databases for semantic retrieval - LLM-powered systems in production: the full lifecycle, including what happens when models behave unexpectedly at scale - LLM validation loops — evaluation pipelines, regression testing, failure analysis, built and operated, not just designed - LangSmith or equivalent at the depth where you've used it to find real bugs, not just generate traces - Full-stack: sufficient depth to make architectural decisions and debug across the sta