AI Engineering Manager

EPAM Systems

We are seeking a hands-on AI Engineering Manager to lead a high-performance team of AI and machine learning engineers in designing, developing and deploying innovative AI-powered products and platforms. This role blends deep technical expertise with strategic leadership, requiring the manager to guide teams in building advanced AI solutions while personally contributing to architecture and system design. The manager will play a key role in shaping the AI strategy and mentoring engineering talent.

Responsibilities

Serve as the senior technical authority for the AI engineering team, guiding architecture, design and implementation of scalable, reliable and secure AI systems
Dedicate significant time to hands-on development, including coding, code reviews and architecting complex systems
Drive modernization of legacy systems by integrating AI capabilities such as RAG systems, code generation and multi-agent workflows
Oversee the entire AI project lifecycle, from conception and experimentation to production deployment and optimization
Establish and enforce best practices for the software development lifecycle, including agile methodologies, CI/CD and automated testing
Collaborate with executive leadership and product management to define AI strategy and roadmap, ensuring alignment with business objectives
Make critical build-vs-buy decisions regarding AI tools and platforms
Manage departmental budgets, resource allocation and vendor relationships
Communicate technical concepts, project progress and risks to both technical and non-technical stakeholders
Lead, mentor and grow a team of AI engineers, fostering a culture of innovation, collaboration and continuous learning
Oversee hiring, onboarding and career development of engineering talent

Requirements

13-15 years of experience in software engineering, with a significant portion dedicated to AI, machine learning or data science
5-8 years of experience in a leadership or management role, leading high-performing engineering teams
Extensive hands-on expertise in Python, Java or C++
Deep expertise in machine learning, deep learning, natural language processing and generative AI
Proven experience designing and building scalable AI infrastructure and MLOps/LLMOps pipelines on cloud platforms such as AWS, Azure and GCP
Strong background in system design, microservices architecture and API development
Bachelor's or Master's degree in Computer Science, Engineering or related field (PhD is a plus)

Nice to have

Experience in a "player-coach" role, with a desire to stay hands-on with technology
Track record of delivering large-scale, complex AI projects from start to finish
Excellent problem-solving skills and ability to navigate ambiguity
Strong communication and interpersonal skills