Automation Engineer

Job Title:

Automation Engineer

Job Description
This role focuses on designing, building, and maintaining automated evidence collection and control-testing pipelines that integrate with cloud, identity, endpoint, ticketing, and source control systems. You will codify control requirements as executable tests, normalize complex data into consistent schemas, and ensure that evidence and control results flow reliably into an internal compliance and controls platform. The position also involves hardening AI-assisted workflows, collaborating directly within an existing production codebase, and documenting your work so that internal teams can maintain and extend it after the engagement.

• Design and build automated evidence collection pipelines that integrate with APIs and event-driven systems across cloud platforms, identity providers, endpoints, ticketing systems, source control, and other tools, ensuring evidence flows into the platform's evidence management and controls modules with minimal manual handling.
• Implement continuous control tests as code by translating control requirements into executable checks against source-system state, running them on schedules or change events, and surfacing pass/fail results and associated evidence artifacts back into the platform.
• Engineer the evidence data layer by normalizing heterogeneous source data into consistent schemas, preserving provenance and timestamps for auditability, and handling pagination, rate limits, retries, and partial failures to keep pipelines robust and reliable.
• Build and test features across internal applications from implementation through QA, working directly in the existing codebase within established patterns, code review processes, and CI/CD workflows.
• Harden AI-assisted workflows such as questionnaire response generation, evidence-to-control mapping, and parity tracking by creating evaluation datasets, scoring rubrics, and regression checks, and by implementing guardrails, structured outputs, and fallbacks where accuracy is critical.
• Instrument and monitor pipelines and automated workflows in production using logging, alerting, and dashboards to detect broken integrations, stale evidence, or output drift before they impact audits, customer responses, or compliance deadlines.
• Document integration designs, data models, control-test logic, evaluation methodologies, and known limitations clearly and comprehensively so that the internal team can maintain, extend, and troubleshoot the work after the engagement.

• At least 5 years of software or automation engineering experience building and shipping production code.
• Strong proficiency with Python and Type Script for production software engineering, including API integrations and automation.
• Hands‑on experience with API development, including working with webhooks, authentication mechanisms, and automated testing.
• Cloud and identity and access management (IAM) experience, preferably with AWS, including working with cloud APIs and infrastructure or configuration tooling.
• Experience building SaaS and system integrations with tools such as Okta, Entra, Jira, Git Hub, Google Workspace, or similar platforms.
• ETL and data pipeline experience, including pulling, normalizing, mapping, and tracking data between systems.
• Comfort working in an existing production codebase, including familiarity with CI/CD pipelines and test automation.
• Production large language model (LLM) integration experience, including designing structured outputs and implementing evaluation and regression testing for AI-assisted workflows.
• Proficiency with tools and workflows related to CI/CD and automated quality assurance.
• Strong technical documentation and written communication skills, with the…