Senior Full-Stack Engineer Python, Temporal & AI Workflows

Role: Senior Full-Stack Engineer — Python, Temporal & AI Workflows

Experience: 10+ Years

Location/Mode of Work: San Francisco - Remote

Visa: USC / GC / GC-EAD

MOI: Skype

Notes :

Must be willing to work in PST Time Zone

Need old LinkedIn with proper connections & details .

Strong Comms skills required as PV and the client panel are screening very thoroughly.

Must have recent financial or supply chain or product-based company experience only.

Majorly product-based and supply chain domain exp req .

Candidates need to clear a HackerRank test.

What you'll do

• Build internal applications and tools end to end — Python backends, React front-ends, and the APIs between them.

• Design and implement AI workflows and AI agents that automate real Finance and Supply Chain processes.

• Model long-running, stateful business processes as durable Temporal workflows — orchestration, retries, human-in-the-loop steps, exception handling.

• Build backend and enterprise integrations (ERPs, finance/supply-chain systems, third-party APIs, internal services).

• Own production support for your systems: monitoring, debugging, incident response, and iterative hardening.

• Translate ambiguous business requirements into reliable, well-scoped software with limited direction.

• Must-have qualifications

• 5+ years building production software, with strong recent Python (async, typing, testing discipline).

• Solid CS fundamentals — data structures, algorithms, complexity — strong enough to pass a rigorous coding interview.

• Backend and API depth: designing, building, and integrating services; handling failure, idempotency, and data consistency.

• Working React proficiency — can build and maintain functional front-ends for internal tools.

• Proven ability to work through ambiguous business workflows independently and ship reliably and quickly.

• Strong written and verbal communication; comfortable defending design decisions with client engineers.

• Legally authorized to work in the US. Strongly preferred

• Hands-on Temporal (or equivalent durable-execution engines like Cadence, Step Functions) — understands determinism constraints, activity/workflow boundaries, signals/queries, durable timers, versioning, worker scaling.

• Experience building AI workflows or agents — LLM orchestration, tool/function calling, retrieval, evals, guardrails.

• Finance and/or Supply Chain domain exposure, or experience with enterprise system integrations.

• Production ownership: on-call, observability (logs/metrics/tracing), safe deploys.

• What makes a candidate stand out

• Clean, testable, idiomatic code and a high personal quality bar — reviewers rarely need to ask twice.

• Can decompose a vague, open-ended problem into a correct, incremental plan and explain the reasoning clearly.

• Fast learner — picks up unfamiliar codebases, domains, and tools quickly.

• Track record of shipping reliable systems in fast-moving, high-stakes environments.

• Nice to have

• Cloud (AWS/GCP), containers/Kubernetes, CI/CD.

• Datastores at scale (Postgres, Redis, Kafka, etc.).

• Experience embedded with or vendored into a demanding client engineering org