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AI Engineering Manager
Posted about 1 month agoViewed
💎 Seniority level: Manager, 5+ years
🔍 Industry: Software Development
🏢 Company: Mechanized AI👥 11-50Artificial Intelligence (AI)Big DataMachine LearningInformation TechnologySoftware
🗣️ Languages: English
⏳ Experience: 5+ years
Requirements:
- 5+ years of hands-on AI engineering (GenAI, Agents, LLMOps, MLOps, Data Science, CV, NLP, etc.)
- 3+ years of AI leadership experience with a dual focus on technical excellence and product management (e.g., AI Product Owner/ AI Product Manager)
- 3+ years managing/implementing MLOps in enterprise-scale AI/ML deployments
- 1+ years in Agentic AI implementation/management (multi-agent systems, generative AI, LLMOps)
Responsibilities:
- Recruit, mentor, and develop a high-performing, diverse AI/ML and Data engineering team—fostering collaboration, continuous learning, and clear performance metrics to drive retention in a fast-paced environment
- Champion technical excellence by applying first principles thinking and data-driven problem solving, enforcing rigorous code reviews, automated testing, and comprehensive documentation while promoting Agentic, MLOps, and LLMOps best practices
- Implement Agile methodologies to conduct regular gap analyses and risk assessments, transforming process deficiencies into stable processes
- Collaborate with the CAIO to define and execute a technical roadmap that balances cutting-edge AI product development with enterprise-grade reliability, security, and performance, while integrating emerging trends
- Oversee the entire AI product lifecycle—from proof-of-concept through production deployment, monitoring, and iterative improvement—ensuring alignment with business objectives, client needs, and industry standards
- Manage product timelines, resource allocation, and deliverables through effective task management, delegation, and milestone tracking, while maintaining high team morale
- Serve as an AI liaison for internal stakeholders, proactively communicating progress, identifying risks, and diffusing tensions through transparent documentation and open dialogue
- Embrace a product owner mindset to prioritize tasks and manage the product backlog, aligning technical development with strategic business goals
- Drive product evolution by providing insights on scalable architecture, governance, and advanced LLM/Agentic techniques, shaping a forward-thinking AI vision that anticipates future trends
- Establish and monitor clear KPIs and performance metrics through regular reviews and retrospectives to ensure accountability and continuous improvement
- Foster cross-functional collaboration across Data, AI, Backend, DevSecOps, QA, and Frontend teams via structured communication and transparent reporting, ensuring cohesive alignment across the organization
- Cultivate innovation by promoting experimentation, calculated risk-taking, and continuous feedback loops that leverage data analytics to refine models, processes, and products
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- Champion technical excellence by applying first principles thinking and data-driven problem solving, enforcing rigorous code reviews, automated testing, and comprehensive documentation while promoting Agentic, MLOps, and LLMOps best practices
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- Collaborate with the CAIO to define and execute a technical roadmap that balances cutting-edge AI product development with enterprise-grade reliability, security, and performance, while integrating emerging trends
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- Embrace a product owner mindset to prioritize tasks and manage the product backlog, aligning technical development with strategic business goals
- Drive product evolution by providing insights on scalable architecture, governance, and advanced LLM/Agentic techniques, shaping a forward-thinking AI vision that anticipates future trends
- Establish and monitor clear KPIs and performance metrics through regular reviews and retrospectives to ensure accountability and continuous improvement
- Foster cross-functional collaboration across Data, AI, Backend, DevSecOps, QA, and Frontend teams via structured communication and transparent reporting, ensuring cohesive alignment across the organization
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Posted about 1 month ago
🧭 Full-Time
🔍 Software Development
🏢 Company: Mechanized AI👥 11-50Artificial Intelligence (AI)Big DataMachine LearningInformation TechnologySoftware
- 5+ years of hands-on AI engineering (GenAI, Agents, LLMOps, MLOps, Data Science, CV, NLP, etc.)
- 3+ years of AI leadership experience with a dual focus on technical excellence and product management (e.g., AI Product Owner/ AI Product Manager)
- 3+ years managing/implementing MLOps in enterprise-scale AI/ML deployments
- 1+ years in Agentic AI implementation/management (multi-agent systems, generative AI, LLMOps)
- Proven ability to manage backlogs, prioritize features, and develop product roadmaps to drive effective execution and continuous improvement
- Experience leveraging customer feedback and market insights (via surveys, usability tests, interviews) to refine product strategy and enhance offerings
- Proven ability to manage and scale remote AI/ML teams (10+ members) in dynamic, high-pressure environments with strong delegation and conflict resolution
- Exceptional product management, resource planning, timeline management, risk mitigation, and cross-functional alignment skills
- Outstanding communication and ethical leadership with a commitment to accountability and continuous improvement
- Proven ability to operationalize AI product management using tools like Jira and Confluence
- Proficiency in English at a C2 level
- Recruit, mentor, and develop a high-performing, diverse AI/ML and Data engineering team—fostering collaboration, continuous learning, and clear performance metrics to drive retention in a fast-paced environment
- Champion technical excellence by applying first principles thinking and data-driven problem solving, enforcing rigorous code reviews, automated testing, and comprehensive documentation while promoting Agentic, MLOps, and LLMOps best practices
- Implement Agile methodologies to conduct regular gap analyses and risk assessments, transforming process deficiencies into stable processes
- Collaborate with the CAIO to define and execute a technical roadmap that balances cutting-edge AI product development with enterprise-grade reliability, security, and performance, while integrating emerging trends
- Oversee the entire AI product lifecycle—from proof-of-concept through production deployment, monitoring, and iterative improvement—ensuring alignment with business objectives, client needs, and industry standards
- Manage product timelines, resource allocation, and deliverables through effective task management, delegation, and milestone tracking, while maintaining high team morale
- Serve as an AI liaison for internal stakeholders, proactively communicating progress, identifying risks, and diffusing tensions through transparent documentation and open dialogue
- Embrace a product owner mindset to prioritize tasks and manage the product backlog, aligning technical development with strategic business goals
- Drive product evolution by providing insights on scalable architecture, governance, and advanced LLM/Agentic techniques, shaping a forward-thinking AI vision that anticipates future trends
- Establish and monitor clear KPIs and performance metrics through regular reviews and retrospectives to ensure accountability and continuous improvement
- Foster cross-functional collaboration across Data, AI, Backend, DevSecOps, QA, and Frontend teams via structured communication and transparent reporting, ensuring cohesive alignment across the organization
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