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