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Mitiga is a Zero-Impact Breach Prevention platform delivering agentic runtime security across cloud, SaaS, identity, and AI infrastructure. The company's detection engine protects the modern stack where traditional endpoint detection tools cannot reach.
You will join the Data team as a Senior Software Engineer, owning the engineering quality and evolution of a large production Python codebase running PySpark on Databricks. This role bridges data engineering, security detection, and AI-driven automation.
Key Responsibilities:
- Harden and extend the production Python codebase through refactoring, module and API design, typing improvements, and test coverage expansion.
- Own and optimize critical PySpark workflows processing massive security datasets across multi-cloud environments, balancing correctness and cost.
- Design data models and queries the detection engine depends on; identify and fix performance bottlenecks.
- Collaborate directly with cyber investigators to translate attacker behavior into production-grade detection logic.
- Integrate AI as a core tool: use AI coding agents (Claude Code) daily and build agentic workflows (n8n or similar) and LLM-backed services on AWS Bedrock or vendor APIs.
- Raise engineering standards across code review, CI/CD practices, and team technical culture.
- Contribute to architectural decisions and technical direction as the platform scales.
The environment is fast-paced and startup-oriented, emphasizing ownership, adaptability, and cross-functional collaboration.
Requirements:
- 5+ years of production Python experience at a company, including typing, refactoring unfamiliar code, module and API design, pytest, packaging, and participation in a real code-review culture.
- Hands-on SQL proficiency: you design schemas and debug slow queries independently, not just read them.
- AI-native mindset: AI coding agents (Claude Code) are part of your daily workflow; you have shipped something real on top of an LLM, including prompt design, structured outputs, orchestrating multi-step or agentic flows, and testing non-deterministic behavior. The specific platform matters less than demonstrated experience.
- Fluent in Git and CI/CD: you can read a failed pipeline and fix it yourself.
- Energized by fast-paced startup environments where ownership, adaptability, and collaboration drive success.
Nice-to-Have:
- AWS experience (S3, IAM, compute) and AWS Bedrock.
- Workflow automation and agent platforms (n8n, LangGraph, Temporal).
- MCP servers or tool-calling integrations.
- Both Spark and Kafka experience.
- Background in security, detection engineering, or SIEM.
