Senior Python

About ZumloZumlo is an always-on well-being companion—one place for immediate help, gentle structure, and progress you can see. We unify mind, body, emotions, and relationships through timely support, a caring community, and personalized guidance that fits real life.What we stand for: Human first • Simple > complex • Privacy & trust • Evidence over hype • Inclusive by defaultThe role (why it’s rare)AI isn’t a bolt-on here—it’s the nervous system of the product. We’re hiring a senior who has already shipped LLM + retrieval to production and wants end-to-end ownership: problem framing, modeling/orchestration, evaluation, privacy/safety, and the Python services that make it real.What you will ownProduct AI (end-to-end)- Build AI across product surfaces: conversational help, guided steps, tailored activities, “what to do next,” summaries/explanations, and safety checks—grounded with retrieval and citations.- Turn fuzzy needs into robust flows: prompt design, tool/function calling, JSON-schema outputs, fallbacks, streaming, controllable tone and safety boundaries.Retrieval & knowledge- Do RAG right: chunking/segmenters, embeddings, vector DBs (FAISS/qdrant/Pinecone/Milvus), hybrid semantic + re-rankers (BGE/ColBERT), dedupe, freshness policies, provenance.Rapid test & evaluation loop- Make eval routine: golden sets, adversarial suites, shadow evals, canaries, online metrics tied to user outcomes. Capture in-app feedback and close the loop weekly.Safety, privacy, governance- PHI/PII redaction, prompt-injection defenses, output guardrails, rate limits, audit trails, safe logging. Clear data-handling notes for the team.Backend & reliability- Own Python services: FastAPI, Postgres (schemas/migrations), Redis, task queues, retries/idempotency, auth/RBAC, feature flags.- Observability first: logs/metrics/traces, alerting that matters, simple SLOs—systems that are predictable and calm.Data & experimentation- Trustworthy event tracking, simple SQL cohorting, per-feature cost/latency dashboards, A/B hooks so product/growth can run honest tests.Exploration & de-risking- Evaluate models/embeddings, inference servers (vLLM/TensorRT-LLM), compression/quantization, token-efficiency. Prove value with small, cheap spikes before big changes.Collaboration & leadership- Partner with product, mobile (React Native/TS), and platform.- Review PRs, write concise docs/runbooks, mentor juniors, and help hire the next 1–2 great engineers.Must-have experience- 7+ years software engineering with 4+ years Python shipping production APIs/services.- Production LLM + RAG you can discuss end-to-end: retrieval, orchestration, evaluation, and user impact.- RAG depth: embeddings, vector DBs (FAISS/qdrant/Pinecone/Milvus), hybrid search, re-rankers, citation strategies.- Backend foundation: FastAPI/Django/Flask, Postgres/SQL, Redis, queues (Celery/RQ), testing (pytest), CI/CD, containers.- Eval mindset: offline metrics + online behavior; sample-size sense; knows when to ship, iterate, or kill.- Security/privacy: least-privilege, secrets, encryption, safe logging; comfortable with sensitive data.Strong plus- Well-being/health context; HIPAA-aware practices.- Azure & Azure DevOps pipelines; GPU inference; streaming responses.- Telemetry for AI: prompt/version tracking, per-feature cost/latency, drift monitors.- Worked across US + India user bases/time zones.How you work (what we value)- Builder energy: ship → measure → iterate.- Creative + logical: playful with ideas, strict with evidence.- Product-curious: start with the user problem and “definition of good.”- Kind, direct, low-ego: crisp commits/PRs, generous feedback.- Owner’s mindset: reliable, documented, observable.Work setup- Remote-first in India, collaborating closely with a small core team.- Preference for Ahmedabad for an eventual in-person cadence; open across India for the right fit.