Senior AI Engineer

We are seeking a Senior AI Engineer to build a central GenAI Platform, enabling rapid development, validation, and deployment of AI agents for hundreds of product teams across the organization. In this role, you will design and deliver full-stack systems, shape platform capabilities, and help accelerate the impact of AI agents across multiple domains. This position is based in Hungary, with relocation support available from EPAM.

• Design and implement full-stack applications, AI agents, and platform components that enable rapid GenAI agent development, validation, and deployment.
• Build developer tooling, CI/CD, and observability for safe, fast iteration (evals, canaries, rollout/rollback, and cost and quality telemetry).
• Apply secure SDLC and privacy-by-design practices (e.g., threat modeling, least privilege).
• Collaborate with product, UX, and domain experts to deliver customer-focused solutions with measurable outcomes.
• Apply current LLM patterns (e.g., RAG, retrieval, routing, tool use, and evaluation) to deliver measurable customer value: faster and more reliable AI systems, reduced time-to-decision, improved trust and safety metrics, and lower cost per query.
• Lead by example by writing high-quality, maintainable code.

• 5+ years of professional software engineering experience.
• Strong full-stack development skills, including hands‑on experience with Type Script and major cloud platforms (AWS, Azure, GCP).
• Expertise in at least one, and proficiency in several, of the following: AI Agent development and evaluation (including LLM platforms and frameworks such as Lang Chain);
  Backend (Python, FastAPI, Type Script) and frontend (Type Script, Streamlit, Gradio) development;
  Cloud platforms and services, CI/CD, and Infrastructure as Code;
  Site Reliability Engineering, quality engineering, and secure SDLC.
• Proven track record of delivering secure, reliable, and scalable cloud-native systems.
• Experience deploying and evaluating AI solutions at scale using advanced integration patterns (e.g., RAG, Agents) and frameworks such as Lang Chain.
• Experience with vector databases (e.g., Qdrant, FAISS, Chroma).
• Strong problem‑solving, ownership, and cross‑functional communication skills.

• Experience designing experiments, conducting A/B tests, and iterating on models based on user feedback.
• Understanding of retrieval systems (e.g., keyword search, vector search, embeddings) and ranking algorithms.
• Familiarity with emerging AI protocols (e.g., MCP, A2A, ACP).
• Experience deploying to cloud AI platforms (e.g., Azure OpenAI, Amazon Bedrock, GCP Vertex AI) or on‑premises solutions (e.g., vLLM).
• Experience with enterprise AI platforms (e.g., AWS Agent Core, Databricks Agent Bricks, Google Agentspace, Azure AI Foundry).
• Experience with observability and monitoring tools/frameworks.

• Python, Type Script, PyTorch, Hugging Face, Lang Chain
• Vector databases (Qdrant, FAISS, Chroma)
• LLM APIs (Azure OpenAI, AWS Bedrock)