Senior AI Engineer / Data Scientist
Actively Hiring
Full-time Posted 3 months ago
Responsibilities
- check_circle Design, build, and deploy Generative AI and Agentic AI solutions from prototyping through production
- check_circle Develop and optimize multi-agent systems using frameworks such as LangGraph, CrewAI, AutoGen, and Semantic Kernel
- check_circle Implement orchestration patterns including planner/executor, supervisor/worker, and tool-calling workflows
- check_circle Design and build RAG pipelines, including embeddings, chunking, hybrid search, and retrieval evaluation for enterprise data grounding
- check_circle Develop orchestration engines supporting multi-step planning, delegation, and fallback paths for agent workflows
- check_circle Implement integration and communication patterns via MCP, A2A, OpenAPI, REST, and gRPC
- check_circle Build production-grade Python APIs and microservices integrating with enterprise systems and AI services
- check_circle Apply observability and monitoring solutions (Langfuse, Arize, Grafana) to ensure system reliability
- check_circle Contribute to solution architecture, best engineering practices, and documentation
Basic qualifications
- Bachelor’s/Master’s in Computer Science, Data Science, or related field with 4+ years’ experience, or Ph.D. with relevant experience
- Strong engineering experience with Python, APIs, microservices, debugging, and code review
- Proven experience building and deploying Generative AI or Agentic AI applications in production
- Deep understanding of LLM concepts, RAG patterns, prompt design, and evaluation methodologies
- Experience with multi-agent orchestration frameworks (LangGraph, CrewAI, AutoGen, Semantic Kernel)
- Familiarity with orchestration strategies like planner/executor and tool calling
- Knowledge of MCP, A2A protocols, and OpenAPI-based integration methods
- Strong experience with cloud environments, ideally Azure (Azure OpenAI, AI Foundry, AI Search)
- Competence in containerized deployments, CI/CD, and MLOps tooling (MLFlow, Airflow)
Preferred qualifications
- Experience with Microsoft Agent Framework, Azure AI Agent Service
- Knowledge of vector databases (Pinecone, Weaviate, Qdrant, Milvus)
- Familiarity with guardrail and AI safety techniques (output filtering, prompt injection defense)
- Experience in distributed systems, event-driven architectures, and workflow engines
- Prior involvement in training, fine-tuning, or experimenting with foundation models
- EPAM Employee Stock Purchase Plan (ESPP)
- Protection benefits including life assurance, income protection and critical illness cover
- Private medical insurance and dental care
- Employee Assistance Program
- Competitive group pension plan
- Cyclescheme, Techscheme and season ticket loans
- Various perks such as free Wednesday lunch in-office, on-site massages and regular social events
- Learning and development opportunities including in-house training and coaching, professional certifications, and courses
- If otherwise eligible, participation in the discretionary annual bonus program
- If otherwise eligible and hired into a qualifying level, participation in the discretionary Long-Term Incentive (LTI) Program
Tags & Focus Areas
Ai Ai Engineer Data Science Generative Ai
About EPAM Systems
Shape the future of global data science infrastructure as a Site Reliability Engineer at EPAM. You'll architect, implement, and support cutting-edge platforms like Alteryx, Dataiku, and Azure Machine Learning that power critical business insights across wealth management, investment banking, and corporate functions.