Generative AI Operations Engineer (GenAI Ops)

We are seeking a highly motivated and experienced Generative AI Operations (GenAI Ops) Engineer to join our innovative team.

In this role, you will be at the forefront of the AI revolution, responsible for building, deploying, and maintaining the operational infrastructure for our cutting-edge generative AI models and services. You will work closely with data scientists, machine learning engineers, and software developers to ensure our GenAI applications — especially complex, multi-agent systems — are scalable, reliable, and efficient across major cloud platforms. If you are passionate about operationalizing large-scale AI systems and want to make a significant impact, this is the role for you.

Feel free to work remotely from anywhere across Lithuania or connect with colleagues at our Vilnius and Kaunas offices.

Responsibilities

• Design, implement, and maintain robust, automated CI/CD pipelines for training, evaluating, and deploying large language models (LLMs) and AI agents
• Design, deploy, and manage sophisticated, multi-agent systems. Ensure seamless Agent-to-Agent (A2A) communication and collaboration between specialized agents to automate complex business processes
• Implement and manage secure, scalable integrations between AI agents and external tools/APIs, leveraging open standards like the Model Context Protocol (MCP) to ensure interoperability
• Utilize AI-powered development tools to accelerate the entire software development lifecycle, from writing infrastructure code and tests to troubleshooting operational issues in cloud environments
• Utilize cloud-native IaC services or cloud-agnostic tools like Terraform to define and manage the infrastructure required for GenAI workloads
• Implement comprehensive monitoring and logging solutions to track model and agent performance, resource utilization, and system health. For agentic systems, this includes tracing the agent's actions and logging the multi-step conversational flow
• Design and implement scalable architectures for model serving and inference. Continuously optimize the performance and cost-effectiveness of our GenAI services
• Implement and enforce security best practices for our GenAI infrastructure and data. Ensure compliance with industry standards and regulations

Requirements

• 3+ years in a DevOps, SRE, or MLOps role with a focus on cloud infrastructure and a background in cloud services (AWS, GCP, Azure)
• Skills in building and managing CI/CD pipelines (Jenkins, GitLab CI, or cloud-native services) and proficiency in at least one scripting language (e.g., Python, Bash)
• Familiarity with IaC tools (e.g., AWS CDK, CloudFormation, Terraform) and containerization/orchestration (Docker, Kubernetes)
• Track record of deploying and operating LLM inference (e.g., vLLM, Triton, TGI, Ray Serve, KServe/Seldon)
• Hands-on experience with LLM/app tracing and metrics (e.g., OpenTelemetry + Langfuse, Arize Phoenix, WhyLabs) and in building evaluation pipelines (offline/online, regression suites)
• Skills in operating retrieval pipelines: embedding generation, indexing/refresh strategies, vector DBs (Pinecone, Weaviate, Milvus, FAISS), and relevance monitoring
• Experience in running multi-agent workflows (LangGraph, CrewAI, AutoGen-like), including state management, retries, rate limits, tool-failure handling, and step-level auditing
• Experience in implementing guardrails: secrets isolation, tool/API permissions, prompt-injection defenses, data leakage prevention, PII redaction, and policy enforcement
• Background integrating agents with external tools using MCP (or similar tool-calling standards) and operating tool registries is a plus
• Fluent in English (B2+ level)

Nice to have

• Master's degree or PhD in Computer Science, AI, Machine Learning, or a related field
• Experience with cloud-native GenAI services like AWS Bedrock, Azure AI Foundry, or Google Vertex AI
• Familiarity with the architecture and operational challenges of Large Language Models (LLMs)
• Experience designing or managing multi-agent systems or complex, orchestrated workflows
• Knowledge of monitoring and observability tools like Prometheus, Grafana, or Datadog
• Relevant cloud or DevOps certifications
• Strong problem-solving skills and the ability to work effectively in a fast-paced, collaborative environment

We offer

• Engineering Heritage: Best-in-class experts sharing a culture of engineering excellence and tackling complex engineering challenges for over 30 years
• Advanced Tech Stack: Innovative projects where you can apply or enhance your expertise in Cloud, Data, AI, and other emerging technologies
• World-Class Clients: Work closely with 340+ of the Forbes Global 2000 on creating disruptive solutions that make a global impact
• Professional Growth: Exceptional support for career development with comprehensive resources for upskilling or reskilling in pioneering practices
• GenAI Community: Strong AI competencies with 600+ experts across 55+ locations driving GenAI-enabled transformation journeys
• Entrepreneurial Culture: If you're passionate and dedicated to improving business transformation, we provide the support you need to bring your ideas to life
• Hybrid Setup: The flexibility to work from any location in Lithuania, whether it's your home or our dynamic offices in Vilnius and Kaunas
• Other Benefits: Additional vacation and trust days, private health insurance, Employee Stock Purchase Plan and more

Salary range €3.8K-€5.7K gross, based on your experience and interview results.

EPAM is a leading global provider of digital platform engineering and development services. For over 30 years, our team has helped leading brands navigate the waves of digital transformation, building solutions that help them stay competitive through constant market disruption.With offices in 55+ countries, EPAM has grown in Lithuania to over 1,300+ talented innovators in just 5 years. We foster creativity and unconventional ways of doing things, welcoming like-minded professionals to join us.