Responsibilities
- Own the architecture and technical delivery of the Semantic Knowledge Graph platform across metadata ingestion, graph modelling, AI agents, and observability.
- Define graph entities, relationships, properties, ontology alignment, serialization formats, bulk loading procedures, and streaming upsert standards.
- Design and implement structured and unstructured metadata extraction pipelines from Collibra and transformation and loading frameworks into Amazon Neptune.
- Build LLM-powered, tool-calling AI agents with multi-hop graph traversal, hybrid vector-graph retrieval, response contracts, and provenance tracing.
- Establish engineering governance for prompt engineering, hallucination mitigation, tool failure handling, context management, and agent evaluation.
- Maintain observability for pipeline lineage, agent traces, latency, cost attribution, and graph coverage gaps.
- Translate business use cases into graph query patterns, agent behaviors, and response contracts with cross-functional stakeholders.
- Present architecture decisions and tradeoffs to senior enterprise audiences and mentor an AI Engineering Analyst.
Requirements
- 12–15 years of progressive experience in data engineering, platform engineering, or AI engineering, including senior technical leadership.
- Production experience with graph databases, preferably Amazon Neptune, or alternatively Neo4j or TigerGraph, including modelling, query optimization, and operational management.
- Practitioner-level experience with Collibra Data Intelligence Cloud, including REST and GraphQL API extraction, glossary, lineage, data quality, classifications, and workflow objects.
- Production experience architecting and delivering LLM-powered agentic systems under real-world load.
- Strong Python engineering skills and command of Gremlin and/or SPARQL.
- Fluency with AWS services including Neptune, S3, Glue, Lambda, Step Functions, OpenSearch, and Amazon Bedrock.
- Healthcare or life sciences expertise involving clinical data governance, regulatory submissions, pharmacovigilance, or pharmaceutical commercial analytics.
- Experience with senior stakeholder engagement, architectural tradeoff management, and cross-functional influence.
- Formal ontology engineering experience with OWL, SKOS, and RDF is desirable.
- Experience with Collibra Protect, Data Quality, or Workflow Automation modules is desirable.
- Familiarity with graph machine learning, including node classification and link prediction, is desirable.
- Experience with semantic interoperability interfaces, ontology APIs, metadata exchange standards, and enterprise data governance programs is desirable.
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About Accenture
Accenture helps the world’s leading enterprises reinvent by building their digital core and unleashing the power of AI to create value at speed for organizations across industries. Our strategy is to be the reinvention partner of choice for our clients and lead in the safe, widespread adoption of AI, and to be the most client-focused, AI-enabled, great place to work in the world. We bring together the talent of our approximately 786,000 people with proprietary assets and platforms, deep process and industry expertise, and leading ecosystem relationships to deliver end-to-end solutions and measurable outcomes at scale. Through our Reinvention Services, we offer broad expertise across Cybersecurity, Digital Core, Finance, Industry and Enterprise, Song, Supply Chain and Engineering, and Talent, with advanced capabilities in AI and Data, Industry and Process, and Technology. We serve approximately 9,000 clients and generated approximately $70 billion in FY25 revenue. Visit us at accenture.com. This LinkedIn company page is moderated. When engaging with Accenture, we encourage everyone to: - Use common courtesy and be respectful of others. - Create your own original content and avoid content that you know to be fraudulent. - Never repost someone else's copyrighted work, unless you have permission. - Never post personal, identifying, or confidential information. We reserve the right to delete comments or posts we deem to be: - Profane, obscene, inappropriate, offensive, abusive material. - Spam, repeated comments and commercial messages and personal advertisements. - Discriminatory or that contain hateful speech of any kind regarding age, gender, race, religion, nationality, sexual orientation, gender identity or disability. - Threats; personal attacks; abusive, defamatory, derogatory, or inflammatory language; or stalking or harassment of any individual, entity or organization. - False, inaccurate, libelous, or otherwise misleading in any way.