Automation Engineer

Position: AUTOMATION ENGINEER
Job Description:

Work location:

Remote, M- F 40 hours a week. We are seeking an Automation Engineer to join our client’s Security Assurance & Trust team. The team is building two internal platforms that are becoming core infrastructure for how the company runs compliance and customer trust at scale, and you’ll play a hands-on role supporting both. You’ll design and build automated evidence collection pipelines, evaluate the quality and reliability of AI generated output, and build and test features directly within these internal applications.

This is a builder’s role, ideal for someone who enjoys moving between infrastructure and integration work and the harder challenge of making sure AI output is trustworthy before it reaches an auditor, a customer, or a teammate who depends on it.

Key Responsibilities:

Design and build automated evidence collection pipelines: API and event-driven integrations that pull evidence from cloud (AWS), identity (Okta/Entra), endpoint, ticketing (Jira), source control, and other systems into the platform’s evidence management and controls (CCF) modules with minimal manual handling. Implement continuous control tests as code: codify control requirements as executable checks against source-system state, run them on a schedule or on change events, and surface pass/fail results and evidence artifacts back into the platform.

Engineer the evidence data layer: normalize heterogeneous source data into consistent schemas, preserve provenance and timestamps for auditability, handle pagination, rate limits, retries, and partial failures so pipelines are reliable, not fragile. Build and test features across the internal applications, from implementation through QA, working directly in the codebase alongside the SATellite engineering lead and within established patterns, code review, and CI/CD.

Harden AI-assisted workflows (questionnaire response generation, evidence-to-control mapping, parity tracking): build evaluation datasets, scoring rubrics, and regression checks so output quality is measured, and implement guardrails, structured outputs, and fallbacks where accuracy matters. Instrument and monitor pipelines and automated workflows in production: logging, alerting, and dashboards that flag broken integrations, stale evidence, or output drift before they affect an audit, a customer response, or a compliance deadline.

Document integration designs, data models, control-test logic, evaluation methodology, and known limitations clearly enough for the SAT team to maintain and extend the work after the engagement

Required Qualifications:

5+ years of hands-on software or automation engineering experience shipping production code, ideally in security, compliance, IT automation, or internal platform engineering. Strong Python and/or Type Script fundamentals: REST/GraphQL API integrations, webhooks, authentication flows (OAuth, service accounts, IAM roles), data pipelines, and automated testing. Hands-on experience with cloud platform APIs and IAM (AWS preferred) and with infrastructure-as-code or configuration tooling, enough to query system state programmatically and reason about what it proves.

Experience building integrations against SaaS and identity systems (Okta, Entra, Jira, Git Hub, Google Workspace, or similar), including handling rate limits, pagination, schema changes, and failure recovery.

Experience with data pipeline or ETL work: pulling structured and unstructured data from source systems, normalizing it, and mapping it reliably into a downstream system with traceability. Comfort working inside an existing codebase rather than greenfield: reading others’ code, following established patterns, and writing tests that hold up in CI. Production experience…