Senior Fullstack Platform Engineer (Backend Focus)

New

Salt AIAI platform

Listing locations: USA, Required to work during US-based time framesFull-TimeSenior

Salary140,000 - 180,000 USD per year

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Job Details

Required Skills: PythonDjangoKubernetesTypeScriptReactRESTful APIsDistributed Systems

Have strong backend and platform experience with Python and Django, APIs, distributed systems, cloud infrastructure, Kubernetes, queues, jobs, and production reliability.
Have fullstack production experience and be comfortable using TypeScript and React to build, debug, or shape frontend product surfaces.
Use AI engineering tools such as Claude Code, Cursor, Codex, or similar systems while understanding and carefully reviewing the code you ship.
Demonstrate judgment in constraining, rejecting, or improving AI-generated code and solutions.
Think in contracts, interfaces, failure modes, permissions, observability, and lifecycle.
Show good judgment about when repeated customer work should become a platform capability.
Translate real-world needs from scientists, data teams, operators, and enterprise stakeholders into engineering decisions.
Write clearly about problems and tradeoffs and help the team make decisions.

Build contracts for agents to call pipelines with typed inputs, structured outputs, streaming status, retries, logs, and auditability.
Model platform concepts, build durable APIs, evolve service boundaries, and improve backend reliability using Python and Django.
Develop Kubernetes-backed deployment patterns, scaling, isolation, runtime behavior, observability, and operational reliability.
Build frontend and backend experiences for configuring, running, inspecting, debugging, and reusing AI workflows.
Develop secure customer data access patterns, retrieval systems, indexing, hybrid search, and APIs that respect enterprise boundaries.
Make distributed AI workflows observable, including what ran, what changed, what failed, why it failed, and possible next actions.
Turn one-off customer implementations into reusable platform capabilities while retaining important domain-specific details.
Improve tools, documentation, test harnesses, internal workflows, and diagnostics for developers and operators.

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