Sr. AI Engineer - Data Pipelines & Context Systems
Reltio
| Company | Reltio |
| Category | Engineering |
| Location | Bangalore |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Senior |
| Salary | Not stated by the employer |
| Posted | 27 Jul 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (greenhouse) |
Description
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!
Job Summary:
We are building a highly specialized Enterprise AI Hub to engineer the "Reltio Brain" - a Context Intelligence Operating System that transforms fragmented institutional knowledge into governed, autonomous action. As the Sr. AI Engineer (Data Pipelines & Context Systems), you will build the governed data, context, and tooling layer that allows Reltio AI systems and embedded AI Business Partners to work safely across enterprise knowledge. This role is centered on data pipeline management, context organization, retrieval quality, and model/tool harnesses. You will connect structured and unstructured sources, maintain freshness and access controls, and create reusable MCP/API-style tools that let AI workflows use the right data with clear provenance. This is not primarily a front-end/UI role. You may build lightweight internal surfaces for review, administration, and workflow handoffs, but the center of gravity is the data and context foundation behind those experiences: ingestion, indexing, permissions, source trust, evaluation, and operational reliability.
Job Duties and Responsibilities:
AI Data Pipeline & Context Architecture
Design and implement production-grade pipelines that ingest, normalize, enrich, and synchronize structured and unstructured enterprise data from sources such as Reltio/MDM, Google Workspace, Slack, Jira/Confluence, transcripts, product systems, and operational datasets.
Build patterns for incremental indexing and vector updates so AI systems can refresh only what changed while preserving lineage, permissions, and source metadata.
Model context boundaries across personal, team, departmental, and enterprise layers so AI systems understand where information came from, why it matters, and who can access it.
Governed MCP/API Tooling:
Build secure MCP/API-style tools and services that expose enterprise data and actions to LLM workflows with clear schemas, guardrails, and audit trails.
Implement OAuth/SSO, RBAC/ABAC, tenant boundaries, and server-side permission checks so retr
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