Posted May 29, 2026
At Reltio®, an SAP Company, we believe data should fuel your success in the enterprise AI era. Our Context Intelligence Platform turns fragmented data into a trusted, connected context so AI agents and systems can act with expert-level judgement at enterprise scale. Reltio’s cloud-native SaaS platform harmonizes, unifies, and governs data across sources and formats—including unstructured data—in real time, turning them into data assets that can be mobilized in milliseconds to any application, user, or AI agent. Trusted by more than 200 of the world’s largest brands across industries such as life sciences, financial services, healthcare, and technology, we fuel frictionless operations and help enterprises accelerate innovation and reduce risk. At Reltio, our values guide everything we do. With an unyielding commitment to prioritizing our “Customer First”, we strive to ensure their success. We embrace our differences and are “Better Together” as One Reltio. We are always looking to “Simplify and Share” our knowledge when we collaborate to remove obstacles for each other. We hold ourselves accountable for our actions and outcomes and strive for excellence. We “Own It”. Every day, we innovate and evolve, so that today is “Always Better Than Yesterday”. If you share and embody these values, we invite you to join our team at Reltio and contribute to our mission of excellence. Reltio has earned numerous awards and industry and analyst recognition for our technology, our culture and our people. Reltio was founded on a distributed workforce and offers flexible work arrangements to help our people manage their personal and professional lives. If you’re ready to work on unrivaled technology where your desire to be part of a collaborative team is met with a laser-focused mission to enable digital transformation with connected data, let’s talk!
As a AI Engineer at Reltio, you will be a core part of the team responsible for building intelligent systems that enhance data quality, automate decision-making, and drive entity resolution at scale. You will work with cross-functional teams to design and deploy advanced AI/ML solutions that are production-ready, scalable, and embedded into our flagship data platform. This is a high-impact engineering role with exposure to cutting-edge problems in entity resolution, deduplication, identity stitching, record linking, and metadata enrichment. Job Duties and Responsibilities:
Architect and build multi-agent systems leveraging frameworks such as LangGraph, Crew AI, AutoGen, etc. - Design and implement LLM-powered task orchestration workflows including chaining, memory, and retrieval components. - Deploy and integrate vector databases for context-aware interactions (e.g., Mulvis, FAISS, Pinecone, Weaviate). - Lead development of intelligent pipelines for autonomous planning, dynamic decision making, and multi-modal extensions. - Collaborate with ML researchers, product managers, and engineers to deliver production-grade AI agents. - Monitor system performance, evaluate key metrics (recall, precision, latency), and drive continuous
improvements.- Act as a technical mentor and advocate for best practices in AI engineering and generative AI development. Skills You Must Have:
Advanced Python programming skills with clean, scalable, and production-ready code. - 2+ years of software engineering/AI experience, with 2+ years focused on LLMs and intelligent agents.
Proven experience with LangGraph, Crew AI, LangChain, or equivalent agent orchestration frameworks. - Deep understanding of LLM internals, prompt engineering, and RAG techniques.
Strong knowledge of vector stores, embeddings, and knowledge retrieval integration. - Ability to deploy and monitor AI services in production (bonus: cloud experience in AWS, GCP, or Azure). Skills Good to Have:
Experience working on real-world autonomous agents, task bots, or AI copilots. - Contributions to open-source agent frameworks or LLM orchestration libraries. - Familiarity with LangChain Expression Language (LCEL), LlamaIndex, or AutoGen agents. - Knowledge of AI evaluation metrics, benchmark tools, and debugging techniques. - Strong problem-solving, communication, and mentorship abilities
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