{"id":470322,"url":"https://alion.io/job/avenga-senior-ai-engineer-4","title":"Senior AI Engineer","company":{"id":181252,"name":"Avenga","domain":"avenga.com","url":"https://alion.io/company/avenga","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Teamtailor","truth_index":{"grade":"B","score":78,"open_postings":28,"ghost_share":0,"stale_share":0.893,"repost_share":0,"time_to_fill_p50_days":53,"computed_at":"2026-10-17T05:46:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Skopje, North Macedonia","Ohrid, North Macedonia","Bitola, North Macedonia"],"countries":["MK"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":48000,"max_usd":124000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":2102},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Anthropic","optional":false},{"name":"Azure","optional":false},{"name":"Embeddings","optional":false},{"name":"GitHub","optional":false},{"name":"LLM","optional":false},{"name":"Milvus","optional":false},{"name":"OpenAI","optional":false},{"name":"pgvector","optional":false},{"name":"Pinecone","optional":false},{"name":"Pytest","optional":false},{"name":"Python","optional":false},{"name":"Qdrant","optional":false},{"name":"RAG","optional":false},{"name":"Rest API","optional":false},{"name":"Weaviate","optional":false},{"name":"Amazon ECS","optional":true},{"name":"AWS","optional":true},{"name":"AWS Fargate","optional":true},{"name":"CI/CD","optional":true},{"name":"Docker","optional":true},{"name":"FastAPI","optional":true},{"name":"GitHub Actions","optional":true},{"name":"LangChain","optional":true},{"name":"Langfuse","optional":true},{"name":"LangSmith","optional":true},{"name":"LlamaIndex","optional":true},{"name":"Mypy","optional":true},{"name":"NLP","optional":true},{"name":"PostgreSQL","optional":true},{"name":"Postman","optional":true},{"name":"pre-commit","optional":true},{"name":"Pydantic","optional":true},{"name":"Swagger","optional":true},{"name":"Terraform","optional":true},{"name":"Trunk-Based Development","optional":true},{"name":"WebSockets","optional":true}],"status":"live","first_seen_at":"2026-07-23T11:27:08Z","employer_posted_date":"2026-07-23","last_verified_at":"2026-10-18T00:00:48Z","board_verified":true,"closed_at":null,"days_open":86,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":86},"description":"Avenga is an international engineering firm helping businesses operate with AI at the core. With 6,000+ experts worldwide, we combine engineering expertise with AI-native thinking to turn ambitious ideas into real-world impact across industries, technologies, and markets. \nAt the core of the role\nYou'll be working on the core engine of a production AI assistant, developing Agentic AI solutions using RAG and LLM orchestration to enable the assistant to move beyond answering questions and safely execute real customer requests.\n\n Core skills you’ll bring\n3+ years building production Python services (async, API design)\n\nExperience designing and building REST APIs (and consuming them); comfortable with request/response modelling, auth, and versioning\n\nHands-on experience building RAG / retrieval-augmented generation systems: not just calling an LLM API, but chunking, retrieval, and grounding answers in sources\n\nExperience with any vector database (e.g. Milvus, Pinecone, Weaviate, Qdrant, pgvector) and an understanding of embeddings and similarity search\n\nWorked with an LLM provider (OpenAI / Azure OpenAI / Anthropic / open models) in production\n\nA habit of evaluating output quality, you can explain how you measured whether a RAG system was good\n\nWrites automated tests as a matter of habit unit and integration testing with pytest (mocking, fixtures)\nComfortable with GitHub in a team workflow, feature branches, pull requests, and code review\n\nNice-to-have:\nLlamaIndex (or LangChain) framework experience\n\nMilvus specifically\n\nAzure OpenAI deployments\n\nLLM observability / tracing (Langfuse, LangSmith, OpenInference)\nFastAPI, Pydantic\n\nWebSocket / streaming APIs for real-time chat responses\n\nAPI tooling and testing: Bruno / Postman, OpenAPI/Swagger; API gateways\n\nAsync & parallel testing and mocking AWS\n\nModern Python tooling: uv, ruff, ty/mypy, pre-commit\n\nCI/CD with GitHub Actions, and trunk-based development with Conventional Commits\n\nAWS (ECS/Fargate, Secrets Manager), Terraform, Docker\n\nMultilingual NLP (Dutch/English)\n\nPeople are at the core of Avenga. We provide equal opportunities regardless of race, ethnicity, gender identity, sexual orientation, disability, age, religion, or any other characteristic. 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