Senior Software Engineer (Python)

New

MitratechCompliance SaaS

Remote USFull-TimeSenior

Salary not disclosed

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Job Details

Experience: A minimum of 5 years of software engineering experience developing SaaS applications.
Required Skills: PythonDynamoDBReactCI/CDAWS Lambda

Have a bachelor’s degree or equivalent experience; an emphasis in engineering, data science, computer science, or information systems is preferred.
Have a minimum of 5 years of software engineering experience developing SaaS applications.
Have strong hands-on experience with Python, React, and AWS, including Lambda and DynamoDB.
Have hands-on experience with LLM application patterns, including prompt design, embeddings, vector search/RAG, tool or function calling, structured outputs, and agent orchestration.
Have experience delivering software with AI coding agents such as Claude Code, Devin, or Codex as a core part of your workflow.
Have experience integrating AI coding agents into CI/CD pipelines with automated quality gates.
Have experience designing evaluation and testing strategies for non-deterministic systems and deciding when AI is appropriate.
Have strong fundamentals in system design, API security, automated testing, and multi-tenant SaaS architecture.
Have clear, precise written communication skills for specifications and documentation that people and AI agents can act on.
Preferred: experience with managed model platforms and provider APIs such as Amazon Bedrock, Anthropic, or OpenAI, and agent frameworks or SDKs.
Preferred: experience shipping and supporting an AI/LLM-powered SaaS feature in production.
Preferred: experience building MCP servers or other AI-agent tool integrations.

Break down product goals into modular engineering tasks with specifications and acceptance criteria for engineers and AI coding agents.
Develop and optimize CI/CD pipelines that use AI agents for code generation, automated testing, and code review, with quality gates and human approval points.
Design and test prompts, specifications, repository context, agent instruction files, reusable skills, and MCP tools.
Measure and improve AI agent output over time.
Review human- and AI-generated code for quality, security, scalability, and domain alignment.
Ensure human- and AI-created design plans follow architectural practices, including modularity and bounded contexts.
Contribute to domain models, technical documentation, and internal knowledge bases.
Write secure code and participate in the on-call rotation, responding to production issues including AI feature degradations.
Help teammates with complex problems and design or architecture challenges, and mentor them in effective and responsible use of AI agents.

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