Lead AI/ML Engineer

We are looking for a Lead AI/ML Engineer to join our AI Center of Excellence (AI CoE). This role combines hands-on delivery of AI, GenAI, Agentic AI, and AI-native engineering solutions with practice development, presales support, mentoring, research, and AI SDLC enablement. The successful candidate will act as a technical leader on client projects while helping strengthen the company’s internal AI capabilities, delivery standards, reusable assets, engineering practices, and AI delivery methodologies.
The role is expected to be split approximately as follows:
— 50% Project Delivery — leading the design and implementation of AI, GenAI, and Agentic AI solutions for clients.
— 50% AI CoE Contribution — supporting presales, capability development, AI SDLC initiatives, mentoring, workshops, internal accelerators, and R&D.

Required for this role

Experience:
5+ years of commercial software engineering experience with substantial hands-on coding responsibilities.
3+ years of hands-on experience designing, building, and delivering AI, Machine Learning, or Generative AI solutions in production environments.
Experience leading technical teams or acting as a Technical Lead on client-facing projects.
Proven experience collaborating with cross-functional teams and communicating effectively with both technical and business stakeholders.

AI & GenAI Expertise:
Deep practical experience with Large Language Models (LLMs), embeddings, Retrieval-Augmented Generation (RAG), AI agents, prompt engineering, and model evaluation.
Proven experience designing and deploying complex AI systems involving agent orchestration, multi-agent architectures, coding agents, and AI-native engineering workflows.
Hands-on experience with modern AI assistants and coding agents such as Claude, GitHub Copilot, Cursor, Windsurf, or similar platforms.
Experience building AI-powered development accelerators and automation frameworks, including prompt management, context engineering, tool integration, skills, agents, feedback loops, and AI SDLC workflows.
Strong understanding of emerging AI engineering practices, model capabilities and limitations, evaluation methodologies, and responsible AI principles.

Software Engineering & Architecture:
Strong software engineering foundation, including software architecture, clean code principles, automated testing, source control, DevOps, CI/CD, and modern software delivery practices.
Proven experience designing scalable, secure, reliable, and maintainable AI-powered systems for production environments.
Ability to incorporate governance, observability, security, and operational considerations into AI solution architectures.

Leadership & Professional Skills:
Strong leadership, mentoring, presentation, facilitation, and stakeholder management skills.
Ability to drive technical decisions, establish engineering best practices, and guide teams through AI solution delivery.
Ability to manage multiple initiatives, adapt quickly to changing priorities, and effectively switch contexts in a fast-paced environment.
Strong written and verbal English communication skills.

Nice to Have:
Experience in presales, solution consulting, proposal preparation, technical workshops, solution estimation, and client-facing architecture discussions.
Experience defining and implementing AI engineering standards, AI SDLC practices, or AI transformation initiatives within engineering organizations.
Anthropic Solution Architect Foundational certification or other recognized AI, cloud, or platform certifications.
Experience with enterprise AI governance, AI observability, AI evaluation frameworks, and agent operations (AgentOps).

Your responsibilities
Project Delivery and Technical Leadership:
Lead the design and delivery of AI, ML, GenAI, and Agentic AI solutions for client projects.
Act as a technical lead for AI agents, copilots, AI-powered workflows, and AI-enabled engineering initiatives.
Define solution architecture, technical approach, implementation standards, and delivery plans.
Guide engineering teams on model integration, retrieval-based solutions, agent workflows, evaluation, monitoring, and deployment.
Lead projects using modern AI-native engineering methodologies, including Specification-Driven Development (SDD), to improve delivery speed, quality, traceability, governance, and engineering productivity.
Translate business requirements into structured specifications, acceptance criteria, and implementation plans that can be consumed by both engineering teams and AI agents.
Review technical designs, architecture decisions, code quality, delivery risks, and AI governance considerations.
Collaborate with client stakeholders, project managers, business analysts, architects, engineers, and QA teams.

Presales and Client Engagement:
Support discovery calls, technical workshops, and client consultations.
Prepare solution concepts, technical proposals, estimates, and delivery approaches.
Contribute to statements of work, proof-of-concept planning, and architecture documentation.
Support sales and account teams with technical expertise during presales activities.

AI SDLC and Practice Development:
Help define and improve company practices for applying AI across the software delivery lifecycle.
Contribute to defining and evolving company standards for AI-native software delivery and Specification-Driven Development.
Create practical approaches for using AI in discovery, requirements, design, development, testing, deployment, and support.
Develop reusable specification templates, evaluation plans, agent instructions, and delivery playbooks.
Contribute to internal frameworks for coding agents, AI evaluations, quality gates, responsible AI delivery, and AI governance.
Support the development of repeatable delivery models for AI and GenAI projects.

Mentoring, Enablement, and Community Leadership:
Mentor engineers, tech leads, and delivery teams in AI, GenAI, Agentic AI, AI SDLC, and SDD practices.
Conduct internal and client-facing workshops on AI-first engineering and AI-enabled software delivery.
Support knowledge sharing and capability growth across the organization.
Participate in technical interviews and hiring activities.

Research and Innovation:
Lead R&D initiatives in GenAI, AI agents, AI SDLC, and AI-assisted software delivery.
Explore new tools, frameworks, cloud services, and delivery practices.
Build prototypes and proof-of-concepts to validate new ideas.
Develop reusable accelerators, frameworks, demos, and delivery assets.

What you get
Your time off
18 paid vacation days and 10 paid sick days annually
10 Ukrainian public holidays
Maternity and paternity leaves
Marriage and Parenthood Package
Additional leave for major life events
Sabbatical leave opportunities

Learning & growth
Sombra University workshops and internal learning programs
Tech Communities and knowledge sharing sessions
Language courses and workshops
Mentorship opportunities

Health & well-being
Sports compensation or health insurance coverage
Participation in races and marathons
Corporate doctor (telemedicine)
Well-being initiatives and workshops

And even more
Company-provided technical equipment
PE administration and tax support
Internal referral program
IT Club loyalty program
Company events and volunteering initiatives

Before you apply
Our recruitment team will carefully review your profile, and if we see a good match with the role, we’ll reach out to you shortly.
If you don’t hear from us within 5 business days, it means we’ve decided to continue the process with other candidates for this position. Thanks for understanding.