AI Practice Lead

Requirements:

• 6+ years experience in AI/ML engineering
• 2+ years experience in GenAI engineering
• 2+ years experience in Lead engineering roles
• Pre-Sales / discovery / project kickoff experience
• Experience selecting the best talent by technical interviewing
• Experience growing the talent by assessing, setting goals and mentoring
• Experience participating in AI talks
• Upper-intermediate high level of English
• Experience with Financial Services & Banking domain will be a plus

Technical Requirements:

• Hands-on experience with Azure / AWS / GCP tools and services for AI and ML
• Proven expertise in LLMs, RAG (including Agentic RAG), AI agents, and prompt engineering.
• Hands-on experience with LangChain, LangGraph, or similar frameworks for agent workflows.
• Experience designing and deploying end-to-end ML pipelines and integrating LLMs into applications
• Practical experience with MLOps practices and building CI/CD pipelines for AI/ML workflows.
• Familiarity with LLM infrastructure, scaling, and deployment best practices.
• Proficiency in Python and ML libraries such as PyTorch or TensorFlow.

Responsibilities:

• Involvement on the projects with the role of Lead AI engineer for project kickoff, consulting and delivering solutions for technical challenges
• Working with Resource Manager to provide the best allocation of AI engineers across projects
• Involvement into Presales calls with potential clients and representing AI service of the company
• Develop and shape AI service offering of Sombra
• Maintain a strong understanding of industry trends and best practices in the AI ecosystem
• Involvement in Discovery phases and assessments for new and existing projects
• Perform tech interviews for new AI engineers and teams, contribute to improving corporate tech interview standards, and focus on continuous professional development of AI stream
• Assessing promotions of AI engineers and improving promotion process
• Growing AI community in the company by organizing regular syncs and events and sharing Sombra culture & values across AI stream
• Effective cooperation with CTO and other Competence Leads (Head of Engineering, QA/AQA, UX, Data)
• Lead the development of scalable, production-ready AI systems with a strong focus on prompt engineering, fine-tuning, and deployment.
• Mentor AI engineers on LLMs, Agentic RAG, LangGraph, and best practices in AI system design and implementation.
• Oversee ML data pipelines and data infrastructure, ensuring performance and reliability with large datasets (SQL/NoSQL).
• Communicate complex AI concepts clearly across technical and non-technical audiences.