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# AI SDLC Engineer

- **Company:** Eliassen Group
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $228,800.0 - $249,600.0
- **Contract:** Permanent contract
- **Skills:** Agile Methodology, Artificial Intelligence, Automation of Tests, Code Generation, Code Review, Continuous Integration, DevOps, Programming Tools, Scrum Methodology, Systems Development Life Cycle, Software Engineering, Generative AI, Software Version Control
- **Published:** October 12, 2026
- **Apply:** https://www.dice.com/job-detail/b42b521c-c6b7-40eb-ab4e-eba585db22da

## About the Role

* Senior-level, hands-on software engineering experience supporting production applications.
 * Demonstrated experience using generative AI or AI-assisted development tools within active software engineering environments.
 * Experience applying AI across multiple stages of the SDLC.
 * Strong understanding of source control, pull requests, automated testing, CI/CD, and DevOps.
 * Experience working directly with Agile or Scrum engineering teams during active sprint delivery.
 * Ability to collaborate on active code, technical decisions, testing, and delivery workflows.
 * Experience assessing engineering processes and implementing practical improvements.
 * Experience improving workflows, quality, productivity, or delivery speed through AI.
 * Understanding of responsible AI principles including accountability, security, quality controls, independent review, traceability, and auditability.
 * Experience developing or implementing engineering standards, AI usage guidelines, governance controls, playbooks, or operating procedures.
 * Experience defining or measuring outcomes related to AI adoption, productivity, velocity, quality, utilization, or production impact.
 * Strong coaching skills and ability to drive adoption through collaboration.
 * Strong written and verbal communication skills for technical and leadership audiences.
 * Based in and authorized to work in the United States.
 * Ability to work remotely with flexible availability across Eastern and Pacific Time zones.

## Description

* Assess current engineering workflows, development tools, and AI usage.
 * Identify opportunities to reduce manual effort and improve engineering productivity through AI.
 * Apply AI-assisted practices across requirements refinement, code generation, automated testing, code review, pull-request validation, and technical documentation.
 * Work directly with engineers on active code, pull requests, testing, and delivery decisions.
 * Integrate AI into existing SDLC, CI/CD, DevOps, and quality-engineering workflows.
 * Coach developers through hands-on implementation and day-to-day collaboration.
 * Establish practical standards and controls for responsible AI-assisted software development.
 * Maintain appropriate human ownership, independent review, traceability, and auditability for AI-assisted changes.
 * Define and track KPIs related to AI adoption, delivery velocity, utilization, quality, and production impact.
 * Create technical standards, playbooks, implementation guidance, and operating procedures.
 * Translate technical findings and outcomes into clear updates for engineering leadership.
 * Help establish an operating model that can be expanded to additional engineering teams.