Automation Engineer

WideNet Consulting Group; Bellevue (WA); Remote; USD 185,976,000 - 201,130,000; Full time

Benefits offered by this job

Health benefits

401K

Employee Assistance Program

Sick leave

Job summary

WideNet Consulting Group is seeking an Automation Engineer to join the Security Assurance & Trust team. You will design and build automated evidence collection pipelines across AWS, Okta/Entra, Jira, and more, ensuring AI outputs are trustworthy before auditors or customers see them.

You will harden AI-assisted workflows, implement tests as code, and monitor production pipelines with dashboards. This is a hands-on role blending infrastructure, integration, and security/compliance.

Qualifications

• 5+ years of hands-on software or automation engineering experience.
• Strong Python and/or TypeScript fundamentals.
• Experience with cloud APIs and IAM (AWS preferred).
• Experience building integrations with SaaS/identity systems.
• Experience with data pipelines or ETL work.
• Production experience integrating LLM capabilities.
• Strong written communication for documenting designs.

Responsibilities

• Design and build automated evidence collection pipelines across cloud and identity systems.
• Implement continuous control tests as code and surface results.
• Engineer the evidence data layer with provenance and reliable schemas.
• Develop features across internal apps with QA and CI/CD.
• Harden AI-assisted workflows with guardrails and evaluation datasets.
• Instrument and monitor pipelines with logging, alerts, and dashboards.
• Document integration designs and data models for maintenance.

Skills

Python

TypeScript

REST/GraphQL

AWS

CI/CD

LLM integration

Data pipelines

Security/compliance

Testing

Tools

Jira

GitHub

Okta/Entra

Cloud APIs

Job description

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 TypeScript 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, GitHub, 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 integrating LLM capabilities into applications, including structured output design and building eval sets or regression checks to measure output quality.
• Strong written communication for documenting technical designs, data models, and evaluation results for a team to maintain going forward.

Nice to Have:

• Prior exposure to GRC or security compliance workflows (SOC 2, ISO 27001, FedRAMP, HIPAA), enough to understand control requirements, evidence, and why traceability matters to an auditor.
• Experience with compliance automation platforms (Vanta, Drata, Secureframe) or open‑source compliance tooling (OSCAL, Cloud Custodian, OPA/Rego, Prowler, Steampipe).
• Experience with Anthropic/Claude or similar LLM APIs, including prompt engineering, tool use, and structured outputs.
• Experience building internal tools or admin platforms and the tradeoffs of a small, fast‑moving user base.
• Familiarity with CI/CD pipelines, containerization, and test automation frameworks for shipping changes safely to a live internal tool.

Pay Range:$65.00 – $70.00 per hour, depending upon experience.
Health & Medical Benefits, 401K, Employee Assistance Program, and Sick Time applicable by state.