AI Engineering Manager

We are building AI capabilities into the full SDLC and need an AI Engineering Manager to lead hands-on delivery at scale. You will embed LLM tooling into engineering workflows, ship production services and integrations, and enable teams with guardrails, best practices, and measurable impact—apply now.
Responsibilities
Design and deliver AI-powered solutions embedded into SDLC workflows across requirements, development, testing, and CI/CD
Build backend services and integrations that enable LLM-based tooling within engineering environments
Create prototypes and mature them into production-ready AI-assisted automation
Implement AI capabilities into CI/CD pipelines, code review processes, and testing frameworks
Identify SDLC use cases with the highest impact for AI enablement
Define best practices for AI-assisted development across teams
Support engineering teams hands-on as they adopt AI tools
Establish guardrails to ensure secure and responsible AI usage
Measure and communicate the impact of AI adoption on cycle time, quality, and productivity
Requirements
Proven background with 9+ years of engineering experience in Python (must-have), with added exposure to Java or Node.js as a plus
Hands-on experience integrating external APIs, including AI/LLM services
Solid knowledge of CI/CD pipelines along with DevOps ways of working
Expert-level understanding of microservices architecture plus Docker and Kubernetes
Strong capability to deliver production-grade services with scalability, monitoring, and logging in mind
Practical experience using LLM APIs and crafting prompts
Deep understanding of end-to-end SDLC processes
Demonstrated examples of boosting developer productivity through tooling
Clear ability to drive adoption of new technical practices across engineering teams
Effective communication skills when working with engineers and stakeholders
Flexibility to turn AI capabilities into actionable engineering improvements
Confidence running demos, workshops, and internal technical sessions