Vetted MLOps Professionals

“Built and shipped an LLM-powered data quality assistant that generates maintainable validation checks from metadata while executing validations via Great Expectations, exposed through FastAPI and integrated into Airflow-managed pipelines. Emphasizes production reliability (structured outputs, guardrails, monitoring, versioning, human review) and works closely with compliance/operations teams to deliver clear, auditable, user-friendly AI outputs.”

“Engineering leader who built and scaled a distributed team (Serbia + US) to deliver an internal multi-tenant Kubernetes-based PaaS, moving a large org from manual ops-driven deployments to automated CI/CD with >99.97% uptime and 100% service adoption. Known for culture change (blameless post-mortems, clear intake via ticketing) and security-first platform practices (tenant isolation, Falco) supporting SOC2 compliance; also operates at exec level with stakeholder communication and fundraising.”

“Senior software engineering leader with 20+ years of management exposure who has alternated between IC and director-level roles, leading teams of up to 25 across AI platform, analytics, Salesforce, and systems software projects. Particularly compelling for roles needing both technical depth and organizational leadership: they have architected systems themselves, built teams in new geographies, and coordinated platform, AI/data, and consumer engineering groups to deliver successful turnkey AI solutions.”

“Built and shipped a production LLM-powered medical scribe that generates structured clinical visit summaries using RAG, strict JSON schemas, and post-generation validation to reduce hallucinations. Experienced in making LLM workflows deterministic and observable (structured logging/metrics/tracing) and in evaluation-driven iteration with metrics like schema pass rate and edit rate; collaborated closely with clinicians and policy stakeholders at Scale AI to drive adoption.”

“Serial entrepreneur who has created several companies, brought them to market, raised as much as $15M, and achieved exits before moving on to new ideas. Combines an academic and institutional background spanning Harvard, MIT, Mass General Brigham, and the Department of War with two decades of consulting experience, and is especially motivated by building impactful technology.”

“Backend/AI engineer who built a production GPU-backed real-time inference API at Nvidia and debugged burst-induced tail latency, cutting P95 by ~29% through dynamic batching and backpressure. Also shipped an end-to-end RAG + agentic operational diagnostics assistant with strict tool controls, evidence citation, confidence gating, and strong production guardrails, plus demonstrated hands-on Postgres optimization (900ms to 40–60ms).”