Senior AI Platform Engineer
- Compensation
- Not disclosed
- Location
- Belgrade, Serbia
- Work setup
- Remote
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Devops
- Posted
Skills
Nice to have
- Familiarity with Neo4j or other graph databases.
- Exposure to MLFlow or another experiment-tracking/model-lifecycle tool.
- Hands-on experience with Prefect (or a comparable orchestrator like Airflow) for building and scheduling data and processing pipelines.
- Working knowledge of LlamaIndex (or a comparable RAG framework) for building retrieval pipelines over enterprise data.
- Experience with knowledge-graph or ontology-backed systems.
- Prior exposure to services-centric (legal, Architecture/Engineering/Construction or ERP domains).
- Experience with Azure AI, Databricks, or similar enterprise data platforms.
Full description
Job Title: Senior AI Platform Engineer
Location: Belgrade Serbia or Lisboa/Porto/Braga, Portugal
Working Model: Hybrid (flexible, depending on candidate location)
Reports to: sa.global Labs Leaderhip
Department: sa.global Labs – Core Team (team working on AI development within sa.global)
Seniority Level: Senior
empower AI Platform - Senior AI Platform EngineerAbout the Role
Anyone can call an LLM API. We're building the harness around it: sa.global Labs is expanding the core team behind empower — our industry-specific agentic AI platform that fuses a domain knowledge graph, a unified data hub, and multi-agent orchestration to automate real enterprise decisions, not demos. We're looking for a Senior AI Platform Engineer to build and operate the scalable foundation underneath it: the APIs, distributed services, data pipelines, and retrieval infrastructure that connect enterprise data, knowledge, and AI capability across the platform.
It's a deliberately opinionated stack — Neo4j for the Business Knowledge Graph, PostgreSQL with pgvector/pg_search for hybrid retrieval, Prefect for pipelines, LangGraph and DSPy powering the agent layer above you — and this is a hands-on senior role: you're building the reliable, secure, production-grade systems that carry real AI workloads for clients across multiple industries, not prototyping in a sandbox.
About empower AI Platform
empower is a proactive agentic intelligence layer. It's built around 3 pillars, and this role touches all of them, with a focus on the backend foundation:
- Corporate Knowledge (Ontology): the structured semantic model of a client's domain that gives agents grounded, domain-correct context.
- Data Hub: the layer that unifies, cleans, and serves enterprise data into the platform.
- Multi-Agent Skills: the orchestration layer where reasoning, tool use, and multi-step automation happens.
Platform Stack
empower is built on a specific, opinionated stack. Prior hands-on experience with these, not just the general category, is what we're screening for:
- Prefect: orchestration and scheduling data and processing pipelines.
- PostgreSQL with pgvector and pg_search extensions: our production vector store and hybrid full text/semantic search layer.
- Neo4j: the graph database underlying the Business Knowledge Graph.
- MLflow: experiment tracking and lifecycle management for models and prompt/agent evaluation runs.
- LlamaIndex: retrieval and RAG pipeline framework.