Principal AI SDLC Coach

Location: Minneapolis, MN (Remote) | Job Type: C2C

About the role

As a Principal AI Driven SDLC Coach, you serve as the senior technical authority responsible for end-to-end coaching and governance of AI-driven full Software Development Lifecycle (SDLC). You design robust engineering guardrail harnesses and deliver structured hands-on coaching covering every SDLC phase. You standardize repeatable, secure, production-grade AI-augmented workflows for engineering teams, mitigate LLM hallucinations, technical debt security vulnerabilities and inconsistent deliverables across the entire development lifecycle while empowering engineers to maximize AI efficiency without compromising software quality compliance and stability.

Responsibilities

• Full AI Driven SDLC Coaching & Hands On Enablement: Lead formal training, 1:1 deep coaching, team workshops and live code clinics covering the complete AI-powered SDLC workflow.
• Security Analysis & Threat Modelling: Train engineers to leverage AI tools for automated vulnerability scanning, attack surface mapping, OWASP compliance checks, data leakage risk assessment at the design phase.
• Code Review Governance: Coach human-in-the-loop AI code auditing; build checklist-driven review frameworks to validate logic correctness, readability, performance and compliance of LLM-generated code.
• Unit & Integration Testing: Train teams to use AI for test case auto-generation, edge case enumeration, mock data creation, automated test coverage validation, and regression test suite construction.
• CI/CD Pipeline AI Integration: Coach embedding AI tools into build pipelines: pre-commit validation gates, in-flight code scanning, test auto-execution, artifact auditing, and deployment approval automation within CI/CD workflows.
• AI SDLC Harness Architecture & Tooling: Build, design, develop and maintain enterprise-grade technical harnesses that enforce guardrails across every SDLC stage; embed automated validation gates to block unvetted AI outputs early in the lifecycle.
• Enforce mandatory human review gates for high-risk modules at every SDLC checkpoint, regardless of AI automation maturity.

Qualifications

Software engineering experience with complete hands-on SDLC delivery. Proven expertise across requirements gathering, security design, implementation planning, formal code review, manual/automated testing, technical writing, and end-to-end CI/CD pipeline design for production systems.