Quick Summary
- Architect ingestion, transformation, indexing, retrieval, and knowledge-enrichment pipelines.- Build production RAG systems using structured, unstructured, graph, and metadata-driven retrieval.
15 years full time educationSummary: Design and build enterprise knowledge foundations that enable accurate, governed, and context-aware AI and agentic systems.
Project Role Description : Assists with the data platform blueprint and design, encompassing the relevant data platform components. Collaborates with the Integration Architects and Data Architects to ensure cohesive integration between systems and data models.
Must have skills : Data Engineering
Good to have skills : NA
Minimum 5 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary:
Design and build enterprise knowledge foundations that enable accurate, governed, and context-aware AI and agentic systems.
Advanced proficiency with Databricks Assistant, GitHub Copilot or Cursor, alongside LlamaIndex, LangChain, Neo4j, Pinecone, Weaviate, Elasticsearch/OpenSearch and cloud vector-search services, to accelerate governed ingestion, knowledge-graph and production RAG engineering.
Must have built and operated production data, search, knowledge, or retrieval platforms. Experience limited to basic vector-database prototypes is insufficient.
Roles & Responsibilities:
- Architect ingestion, transformation, indexing, retrieval, and knowledge-enrichment pipelines.
- Build production RAG systems using structured, unstructured, graph, and metadata-driven retrieval.
- Define document parsing, chunking, taxonomy, ontology, entity resolution, and lineage strategies.
- Implement access-aware retrieval, freshness controls, quality checks, and auditability.
- Optimize retrieval quality, latency, scale, and cost.
- Partner with AI engineers on context construction and grounding.
- Mentor engineers and define reusable knowledge-engineering standards.
Professional & Technical Skills:
- Python, SQL, distributed processing, and orchestration.
- Vector search, hybrid retrieval, knowledge graphs, metadata, and semantic modeling.
- Document pipelines, search, data quality, lineage, and access control.
- Cloud, APIs, CI/CD, observability, and performance engineering.15 years full time education
Visit us at www.accenture.com
We believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, military veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by applicable law. Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities.
Location & Eligibility
Listing Details
- Posted
- September 21, 2026
- First seen
- September 29, 2026
- Last seen
- September 29, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 32%
- Scored at
- September 30, 2026
Signal breakdown
Stay ahead of the market
Get the latest job openings, salary trends, and hiring insights delivered to your inbox every week.
No spam. Unsubscribe at any time.