Overview
We are seeking a highly skilled Senior AI Engineer with strong expertise in Kubernetes and vector database technologies to join our team. In this role, you will design, build, and scale production-grade AI systems, working with cutting-edge LLM frameworks, embeddings, and cloud-native infrastructure to deliver robust and high-performance solutions.
Responsibilities:
- Deploy and manage Milvus vector databases, including schema design and index tuning (HNSW, IVF-FLAT)
- Build and maintain embedding and LLM pipelines using OpenAI API, Hugging Face, or Cohere
- Manage Kubernetes clusters, Helm charts, and containerized microservices in production
- Develop and maintain Docker containerization workflows, including multi-stage builds and registry management
- Design and deliver production-grade Python applications, integrating with Go, Java, or C++ where required
- Integrate object storage systems such as AWS S3, MinIO, or Google Cloud Storage
- Evaluate and implement alternative vector database solutions, including Qdrant, Pinecone, and Weaviate
- Collaborate cross-functionally with team members to deliver reliable, scalable AI services
- Ensure operational excellence, observability, and performance of deployed AI workloads
Required Qualifications:
- Bachelor's degree in Engineering with 5+ years of relevant experience
- Expertise in Milvus deployment, schema design, and index tuning (HNSW, IVF-FLAT)
- Familiarity with vector database alternatives such as Qdrant, Pinecone, Weaviate, PGVector, or Chroma
- Proficiency in building embedding and LLM pipelines using OpenAI API, Hugging Face, or Cohere
- Skills in Kubernetes cluster management, Helm charts, and containerized microservices
- Background in Docker containerization, multi-stage builds, and registry management
- Production-level Python development 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 with strong team collaboration abilities
- Proficiency in English at an Upper-Intermediate level (B2) or higher
Benefits:
- 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
- Opportunity to work abroad for up to two months per year
- Relocation opportunities within our offices in 55+ countries
- Corporate and social events
- Leadership development, career advising, soft skills and well-being programs
- Certifications, including GCP, Azure and AWS
- Unlimited access to LinkedIn Learning and Udemy
- Free English classes with certified teachers
- Participation in the Employee Stock Purchase Plan
- Monetary bonuses for engaging in the referral program
- Comprehensive medical & family care package
- Four trust days per year for personal needs
- Discounts for fitness clubs
- Benefits package (hotels, restaurants, stores and services)
Nice To Have:
- Experience supporting large-scale RAG applications and multi-agent platforms
- Hands-on familiarity with LangChain, LlamaIndex, or custom pipelines
- Understanding of GPU scheduling, resource optimization, and inference acceleration
- Production experience with hybrid search, metadata filtering, and index tuning
- Implementation of LLM evaluation, governance, tracing, and monitoring tools
- Familiarity with CI/CD pipelines, Infrastructure-as-Code, and cloud-native deployment practices
- Prior work experience in the Oil and Gas industry
- Experience with Dataiku DSS
- Knowledge of SRE practices
- AI Solution Engineering
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