Lead AI Engineer (EPAM SISTEMOS, UAB)

Job description:
We are looking for a Lead AI Engineer to design and deliver AI solutions, including chatbots, Q&A systems, and workflow systems for agents.
This position requires staying informed about LLM advancements and driving innovation in AI projects. Join us to expand your expertise in AI engineering and create impactful solutions tailored to client needs.
_This position offers hybrid setup with the flexibility to work from any location in Lithuania, whether it's your home or our dynamic offices in Vilnius and Kaunas._
Design AI applications such as chatbots, Q&A platforms, and agent workflows
Collaborate with clients to identify needs, opportunities, and recommend LLM-based solutions
Develop data pipelines, prompt strategies, and datasets to support effective AI models
Evaluate AI systems to ensure accuracy, security, scalability, and compliance with industry standards
Research and validate technical feasibility while demonstrating business value
Stay informed about LLM technologies, frameworks, and methodologies to improve solutions
Requirements:
Proficiency in Python and experience with web frameworks like FastAPI
Background in leading and mentoring engineering teams
Understanding of AI development lifecycles
Flexibility to use rapid UI prototyping tools like Streamlit or Gradio
Familiarity with LLM platforms and APIs such as OpenAI, Anthropic, Amazon Bedrock, and Gemini, along with frameworks like LangGraph and LlamaIndex
Knowledge of advanced AI integration patterns like RAG and Agents
Skills in deploying AI solutions at scale with a focus on performance and cost-efficiency
Experience assessing generative AI quality using retrieval, classification, or LLM-based metrics
Proven background in AI engineering and delivering machine learning-based solutions
Competency in problem-solving with strong attention to detail
Strong written and verbal English communication skills (B2+)
Nice to have
Background in designing experiments and conducting A/B testing for model optimization
Understanding of retrieval systems, vector search, and ranking algorithms
Familiarity with protocols like MCP, A2A, and ACP
Experience deploying AI solutions to cloud platforms such as Azure OpenAI, Amazon Bedrock, or GCP Vertex AI; flexibility to leverage on-premise options like vLLM
Background in enterprise AI platforms such as AWS AgentCore, Databricks AgentBricks, or Azure AI Foundry
Skills in using observability and monitoring frameworks and tools
Company offers:
Engineering Heritage: Best-in-class experts sharing a culture of engineering excellence and tackling complex engineering challenges for over 30 years
Advanced Tech Stack: Innovative projects where you can apply or enhance your expertise in Cloud, Data, AI, and other emerging technologies
World-Class Clients: Work closely with 340+ of the Forbes Global 2000 on creating disruptive solutions that make a global impact
Professional Growth: Exceptional support for career development with comprehensive…