EPAM Systems
Senior AI Engineer
- Compensation
- Not disclosed
- Location
- Armenia, Georgia, Kazakhstan, Kyrgyzstan, Uzbekistan
- Work setup
- Remote
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Ai engineering
- Posted
Skills
Must have
- 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
Full description
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
Benefits
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 home