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Senior AI Engineer

EPAM·Salary not specified

Primary stack

LangChainDockerLlamaIndexKubernetesPythonAIRAGSEO

Nice to have's

Background in supporting large-scale RAG applications and multi-agent platformsFamiliarity with LangChain, LlamaIndex or custom LLM orchestration pipelinesUnderstanding of AI observability through LLM evaluation, governance, tracing and monitoring toolsKnowledge of CI/CD pipelines, Infrastructure-as-Code and cloud-native deployment practicesPrior work experience in the Oil and Gas industry along with Dataiku DSS and SRE practices

Job description

Senior AI Engineer

Senior · Hybrid · Armenia, Georgia, Kazakhstan, Kyrgyzstan, Uzbekistan

About the Role

We are seeking a Senior AI Engineer to design, deploy, and optimize cutting-edge AI infrastructure powering large-scale GenAI applications. In this role, you will work with vector databases, LLM frameworks, and cloud-native technologies to build robust, production-grade systems that drive intelligent solutions across the organization.

Responsibilities

  • Deploy and manage Milvus vector databases including schema design and index tuning with HNSW and IVF-FLAT
  • Build embedding and LLM framework pipelines leveraging OpenAI API, Hugging Face, or Cohere
  • Manage Kubernetes clusters, Helm charts, and containerized microservices for scalable orchestration
  • Implement Docker containerization with multi-stage builds and registry management
  • Develop production-level applications in Python along with Go, Java, or C++
  • Integrate object storage systems including AWS S3, MinIO, or Google Cloud Storage
  • Support large-scale RAG applications and multi-agent platforms
  • Optimize compute and inference through GPU scheduling, resource optimization, and inference acceleration
  • Drive search optimization with hybrid search, metadata filtering, and index tuning
  • Collaborate effectively with the team to deliver high-quality solutions

Requirements

  • B.Tech/B.E in Engineering with 5+ years of relevant experience
  • Expertise in Milvus deployment, schema design, and index tuning (HNSW, IVF-FLAT)
  • Familiarity with Qdrant, Pinecone, Weaviate, PGVector, or Chroma
  • Proficiency in OpenAI API, Hugging Face, or Cohere for embeddings and LLMs
  • Skills in Kubernetes cluster management, Helm charts, and containerized microservices
  • Competency in Docker containerization, multi-stage builds, and registry management
  • Production-level proficiency in Python along with Go, Java, or C++
  • Knowledge of object storage integration including AWS S3, MinIO, or Google Cloud Storage
  • Excellent verbal and written communication skills

Nice to Have

  • Background in supporting large-scale RAG applications and multi-agent platforms
  • Familiarity with LangChain, LlamaIndex, or custom LLM orchestration pipelines
  • Understanding of AI observability through LLM evaluation, governance, tracing, and monitoring tools
  • Knowledge of CI/CD pipelines, Infrastructure-as-Code, and cloud-native deployment practices
  • Prior work experience in the Oil and Gas industry along with Dataiku DSS and SRE practices

What We Offer

  • 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, and more

About the Company

We connect like-minded people: Delivering innovative solutions to industry leaders, making a global impact.

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