AI Data Engineer

AI Data EngineerProven experience as a software engineer with strong proficiency in Python and/or Java, writing clean, scalable, production-grade code. Solid experience designing and building microservices and RESTful APIs in distributed, cloud-based environments. Experience designing, implementing, and extending AI agentic systems, including tool use, planning, and autonomous decision-making workflows. Experience building multi-agent systems where multiple agents collaborate, delegate, and coordinate to complete complex tasks. Hands-on experience building conversational or chat systems with both short-term (session) and long-term (persistent) context management. Experience building Retrieval-Augmented Generation (RAG) systems – including document ingestion, chunking strategies, vector stores, and retrieval pipelines. Experience building MCP servers Experience integrating agentic systems with external APIs, third-party services, and enterprise data sources. Strong understanding of security in agentic systems – authentication, authorization, least-privilege access, prompt injection defense, and audit logging. Knowledge of relational databases (e.g. PostgreSQL, Microsoft SQL Server) and vector databases (e.g. Qdrant, Pinecone, pgvector, Weaviate). Experience using system and performance monitoring tools (e.g. New Relic, Datadog). Proficient in Git and comfortable working in CI/CD-driven development workflows. Excellent critical-thinking, communication, and personal leadership skills. Self-starter with the ability to deliver with minimal supervision. BSc/BA in Computer Science or a related degree.