Senior AI Engineer, Agentic and RAG Systems

We are seeking a hands-on Senior AI Engineer who designs, builds, and operates production GenAI systems – agentic workflows, RAG pipelines, and LLM-backed services with real users and real SLAs. This is an engineering role, not a research role. The bar is reliability, latency, cost, observability, and safe deployment at scale, with end-to-end ownership from architecture through on-call. Typical workloads include enterprise knowledge platforms, conversational analytics, agentic automation, and LLM-augmented data products.

Experience the freedom of remote work from anywhere in Georgia, whether from the comfort of your home, our modern offices in Tbilisi and Batumi or a coworking space in Kutaisi.

Responsibilities

• Design agent orchestration (graph/state, conditional routing, tool calling, memory, checkpointing) in LangGraph / LangChain or equivalent
• Build production RAG end-to-end: chunking, embeddings, vector stores, hybrid retrieval, reranking, caching, and grounded synthesis
• Own Python / FastAPI services – async, SSE streaming, session handling, and structured error contracts
• Instrument with tracing and evaluation harnesses (MLflow, OpenTelemetry, or equivalent) for accuracy, cost, and regression
• Ship on Docker + Kubernetes (EKS/AKS/GKE) via CI/CD with test, eval, and canary gates
• Drive LLM cost engineering – model routing, prompt optimization, caching, token accounting, and build-vs-buy decisions
• Apply GenAI safety & governance: hallucination control, prompt-injection defense, PII handling, and HITL where required
• Partner with data engineering on semantic layers and pipelines (PySpark / SQL where applicable)

Requirements

• 5+ years in software engineering, with 2+ years shipping production LLM / agentic systems (not POCs or research)
• Proficiency in Python and FastAPI (async, REST, SSE)
• Production expertise in LangChain and LangGraph (or equivalent serious production experience with LlamaIndex, AutoGen, or MCP stacks)
• Background in production RAG: embeddings, chunking, and hybrid retrieval with reranking and caching
• Skills in vector databases such as Pinecone, Weaviate, pgvector, OpenSearch, or Databricks Vector Search
• Knowledge of at least one major LLM provider in production – AWS Bedrock (preferred), OpenAI / Azure OpenAI, or Anthropic – with model selection and routing trade-offs
• Competency in Kubernetes and Docker in real production environments (EKS/AKS/GKE)
• Expertise in cloud engineering on AWS
• Familiarity with observability and tracing tools (MLflow, LangSmith, OpenTelemetry), evaluation harnesses, and latency/cost ownership
• Capability to build CI/CD for AI systems (GitHub Actions, Jenkins, or equivalent) with test/eval gates
• Strong written and spoken English (B2 level); able to own design discussions with engineering and business stakeholders independently

Nice to have

• Databricks depth – MLflow (tracking & serving), Vector Search, Unity Catalog / Metric Views, PySpark / SQL
• Experience with LLM fine-tuning – PEFT, LoRA, QLoRA
• Understanding of MCP servers and tool integration
• Qualifications in GenAI governance & FinOps – auditability, prompt-injection hardening, PII, and token cost in regulated environments
• Background in classical ML / DL – NLP, BERT-family, time-series, and CV

We offer

• We connect like-minded people
• Delivering innovative solutions to industry leaders, making a global impact
• Enjoyable working environment, whether it is the vibrant office or the comfort of your own home
• Opportunity to work abroad for up to two months per year
• Relocation opportunities within our offices in 55+ countries
• Corporate and social events
• We invest in your growth
• Leadership development, career advising, soft skills and well-being programs
• Certifications, including GCP, Azure and AWS
• Unlimited access to EPAM's internal learning database
• Free English classes with certified teachers
• We cover it all
• Participation in the Employee Stock Purchase Plan
• Monetary bonuses for engaging in the referral program
• Comprehensive medical & family care package
• Five trust days per year (sick leave without a medical certificate)
• Benefits package (sports activities, a variety of stores and services)
  

EPAM is global leader in AI transformation engineering and integrated consulting, serving Forbes Global 2000 companies and ambitious startups. With over thirty years of expertise in custom software, product and platform engineering, we empower our clients to become AI-Native enterprises, driving measurable value from innovation and digital investments.