Senior AI Engineer (Agentic AI & ML)
Senior AI/ML engineer at Avenga's Sofia R&D team building production-grade AI products around LLMs and agentic AI — designing end-to-end systems, RAG pipelines, multi-agent workflows, and Python/FastAPI backends using LangChain/LangGraph, vector databases, and Docker.
- Compensation
- Not disclosed
- Location
- София, BG
- Work setup
- Hybrid
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 6+ years
- Category
- Ai engineering
- Posted
Skills
Must have
- 6+ years of commercial experience building Machine Learning systems
- Proven ML technical leadership — understanding business problems, selecting ML approaches, designing end-to-end solutions
- Hands-on experience with agentic orchestration frameworks (LangGraph, LangChain, or similar)
- Experience designing multi-agent systems, orchestration workflows, state management, tool calling, and structured outputs
- Experience building production-grade applications using LLMs (OpenAI, Gemini, Anthropic or similar)
- Strong understanding of RAG, embeddings, semantic search, retrieval optimization, prompt engineering and context management
- Experience with vector databases (Vertex AI RAG Engine, Pinecone, FAISS, Weaviate or similar)
- Strong Python development skills
- Experience building APIs with FastAPI (or similar frameworks)
- Experience with async programming and long-running backend processes
- Experience designing structured data models using Pydantic (or similar validation frameworks)
- Experience with Docker
- Comfortable working independently in fast-changing R&D and Proof-of-Concept environments
- Strong ownership mindset and excellent problem-solving skills
- Experience using AI-assisted development tools for coding, debugging, refactoring, and documentation
Nice to have
- Experience with Google Cloud Platform
- Hands-on experience with Vertex AI and Gemini
- Experience with Vertex AI RAG Engine
- Experience with AWS or Azure and willingness to work with GCP
- Experience combining LLMs with Computer Vision, signal processing, or other multimodal AI systems
- Experience fine-tuning foundation models or adapting open-source LLMs
- Experience designing evaluation and benchmarking pipelines for AI systems
Full description
This is us
At Avenga, we believe that human creativity empowers technology that matters. Operating globally, our 6000+ specialists provide a full spectrum of services, including business and tech advisory, enterprise solutions, CX, UX and Ul design, managed services, product development, and software development.
This is the job
We're looking for a Senior AI Engineer / ML Engineer to join an R&D team building next-generation AI solutions based on Large Language Models and agentic AI.
This is not a traditional ML engineering role. You'll work on rapidly evolving AI products, combining modern LLM capabilities with strong Machine Learning fundamentals to design production-ready solutions. You'll be expected to evaluate business problems, choose appropriate ML approaches, architect end-to-end systems, and independently drive ideas from concept to deployment.
If you enjoy solving complex engineering problems around LLMs and agentic AI, experimenting with new technologies, and turning research into practical products, we'd love to hear from you.
This is the team
You'll join a senior AI engineering team working in a fast-moving R&D environment where experimentation, ownership, and rapid iteration are part of everyday work.
The team designs and delivers production AI systems based on LLMs, agentic workflows, and modern Machine Learning techniques. Engineers are expected to take ownership of technical decisions, collaborate closely with architects and product stakeholders, and continuously evaluate new approaches as the technology evolves.
This role offers the opportunity to work on cutting-edge AI products while having a real impact on both technical direction and product design.
This is you**
- 6+ years of commercial experience building Machine Learning systems.
- Proven ML technical leadership experience — the ability to understand business problems, select appropriate ML approaches, design end-to-end solutions, and make technical decisions beyond simply implementing models.
- Strong hands-on experience with agentic orchestration frameworks such as LangGraph, LangChain, or similar.
- Experience designing multi-agent systems, orchestration workflows, state management, tool calling, and structured outputs.
- Hands-on experience building production-grade applications using Large Language Models (OpenAI, Gemini, Anthropic or similar).
- Strong understanding of:
- Retrieval-Augmented Generation (RAG)
- embeddings