Note: The job is a remote job and is open to candidates in USA. EPAM Systems is seeking a Lead AI Engineer to design, build, and scale cutting-edge AI applications powered by large language models. In this role, you will partner with clients to deliver tailored LLM-driven solutions, architect agentic systems, and drive the adoption of emerging AI technologies across enterprise environments.

Responsibilities

• Design, implement and maintain end-to-end AI applications, including chatbots, Q&A platforms, agent workflows and other LLM-driven solutions
• Collaborate directly with clients to understand their needs, identify opportunities and recommend tailored AI/LLM solutions that drive business value
• Architect and optimize robust data pipelines, prompt strategies and datasets to ensure effective, accurate and scalable AI models
• Evaluate, monitor and refine AI system performance, ensure outputs are accurate, secure, scalable and compliant with industry regulations and best practices
• Conduct research, design experiments and perform rapid prototyping to validate technical feasibility and demonstrate the business value of AI solutions
• Stay current with evolving LLM technologies, frameworks, protocols (such as MCP, A2A, ACP) and methodologies, continuously improve solution quality and client outcomes
• Design and implement agentic systems with frameworks such as LangChain, LangGraph and Semantic Kernel, integrate with vector databases and advanced memory architectures
• Develop and maintain APIs and system integrations for production-grade AI applications, including enterprise system integration (CRM, ERP, databases)
• Deploy AI solutions at scale, consider performance, cost-efficiency, maintainability, observability and security (including guardrails and prompt injection prevention)
• Implement and monitor retrieval systems (keyword search, vector search, embeddings), ranking algorithms and agent evaluation frameworks
• Use MLOps/AIOps practices for agentic systems and ensure robust observability and monitoring of deployed solutions
• Clearly communicate complex technical concepts and AI strategies to both technical and non-technical stakeholders, iterate on models based on user feedback

Skills

• Strong proficiency in at least one modern programming language (such as Python, Java, C#, Go, etc.); experience with web frameworks like FastAPI or similar is a plus
• Deep understanding of the AI application development lifecycle, including production deployment, system integration and rapid UI prototyping (Streamlit, Gradio or similar)
• Familiarity with major LLM platforms and APIs (OpenAI, Anthropic, Amazon Bedrock, Gemini) and related frameworks (LangChain, LangGraph, LlamaIndex, Strands Agents, etc.)
• Knowledge of advanced AI integration patterns (e.g., RAG, agent orchestration, tool calling), retrieval systems (keyword/vector search, embeddings) and ranking algorithms
• Experience to deploy AI solutions at scale, with a focus on performance, cost-efficiency, maintainability, observability and security (including guardrails and prompt injection prevention)
• Proven ability to evaluate generative AI quality with retrieval/classification scores, LLM-based evaluation, agent evaluation metrics and A/B testing
• Experience with vector databases (Pinecone, Weaviate, ChromaDB, FAISS) and semantic/hybrid search
• Experience to design experiments, conduct A/B tests and iterate on models based on user feedback
• Experience with enterprise system integration (CRM, ERP, databases) and deployment to cloud AI platforms or on-premise solutions
• Experience with observability and monitoring tools/frameworks, and application of MLOps/AIOps practices for agentic systems
• Familiarity with emerging protocols (MCP, A2A, ACP) and advanced memory architectures
• Proven experience in AI engineering and delivery of ML-based solutions in production environments
• Strong problem-solving skills, attention to detail and ability to work independently and collaboratively
• Excellent communication, collaboration and interpersonal skills, with the ability to explain complex technical concepts to non-technical stakeholders

Benefits

• Career plan and real growth opportunities
• Unlimited access to LinkedIn learning solutions
• Constant training, mentoring, online corporate courses, eLearning and more
• English classes with a certified teacher
• Support for employee’s initiatives (Algorithms club, toastmasters, agile club and more)
• Enjoyable working environment (Gaming room, napping area, amenities, events, sport teams and more)
• Flexible work schedule and dress code
• Collaborate in a multicultural environment and share best practices from around the globe
• Hired directly by EPAM & 100% under payroll
• Law benefits (IMSS, INFONAVIT, 25% vacation bonus)
• Major medical expenses insurance: Life, Major medical expenses with dental & visual coverage (for the employee and direct family members)
• 13 % employee savings fund, capped to the law limit
• Grocery coupons
• 30 days December bonus
• Employee Stock Purchase Plan
• 12 vacations days
• Official Mexican holidays, plus 5 extra holidays (Maundry Thursday and Friday, November 2nd, December 24th & 31st)
• Monthly non-taxable amount for the electricity and internet bills

Company Overview