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# Senior Python Engineer

- **Company:** Shield AI
- **Location:** San Diego, CA, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Query Performance, Adobe InDesign, Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Audit Trail, Automation of Tests, Code Review, Databases, Continuous Integration, Cursor, Identity and Access Management, Python (Programming Language), Key Management, PostgreSQL, OAuth, OpenID, Management of Software Versions, Web Application Frameworks, Openapi, Claude Code, AI Coding Agents, Backend, Cloudformation, Fastapi, Build Management, Pytest, Integration Tests, Kubernetes, Infrastructure Automation Frameworks, Machine Learning Operations, Restful APIs, Terraform, Pagination, Code Restructuring
- **Published:** November 13, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pyvwqlwbwl

## About the Role

* 5+ years building and operating backend services in production, with strong Python and FastAPI or a comparable async web framework.
 * REST API design: structured errors (RFC 9457), pagination, versioning and idempotent writes.
 * PostgreSQL schema design, query performance, versioned schema changes with tested rollbacks, and optimistic concurrency.
 * Experience turning written specifications and acceptance criteria into automated tests, with pytest, integration tests against a real database, and contract tests against OpenAPI.
 * Availability to work from 8:00 AM Kyiv time, ensuring 3-4 hours of overlap with the China-based team.

Nice to have

 * Integration with external services: client design, retries, background jobs and long-running workflows.
 * Security: OAuth 2.0 and OIDC tokens, deny-by-default authorization, secrets management, and audit logging that attributes every write.
 * MLOps experience: model registries, training or packaging pipelines, model deployment and monitoring.
 * Workflow or job orchestration, such as Step Functions, Airflow or Argo Workflows
 * Refactoring a large existing service in place
 * Empathy for the engineers who call your APIs: you design for their workflow and act on their feedback.
 * Experience writing specifications, prompts or agent instructions that other engineers and agents work from.
 * Clear writing in design documents, decision records and pull requests, and constructive code review.

## Description

Grid Dynamics is looking fo a backend engineer for the MLOps Platform team. You will design and build REST APIs and the PostgreSQL schema behind them. You will integrate with ML pipeline, model registry and deployment services: starting long-running jobs, tracking them and recording their results. Authorization, validation and an audit trail are built into every write.

We work spec-first and AI-assisted. A written design and an OpenAPI contract are the source of truth, decisions are recorded as architecture decision records, and every task arrives with its acceptance criteria in a form an AI coding agent can work from directly. You will direct agents from the specification through unit, integration and contract tests to a reviewed pull request, review what they write critically, and own the result. CI checks the running API against its published contract.

You will own your services in production: deploy them through CI/CD, instrument them, set alerts, take part in on-call, and release with a rehearsed rollback. You will also make the platform easy to adopt, with clear API documentation, error messages that say what to do next, and support for the teams that build on it.

Responsibilities

 * Daily, hands-on use of AI coding agents such as Claude Code or Cursor: giving them the right context, and reviewing their output critically rather than accepting it.
 * Deploying and running services on AWS: containers on ECS or Kubernetes, managed PostgreSQL, IAM and networking, infrastructure as code with Terraform or CloudFormation, and CI/CD pipelines that build, test and deploy every change with safe rollout and rollback.
 * Production observability: structured logs, metrics, tracing, alerting and runbooks, and calm incident response.