Domain Intelligence Engineer - Document Management Platform (Vice President)

JPMorgan Chase; Wilmington (DE); On-site; USD 180,000 - 240,000; Full time

Job summary

JPMorgan Chase in Wilmington, United States seeks a Vice President Domain Intelligence Engineer to shape governance for enterprise document management tech, build AI tooling for faster, evidence-based assessments, and align platform capabilities with organizational needs.

You will own day-to-day governance, develop a guided knowledge base, and implement RAG and agentic workflows to accelerate evaluations with traceable outputs, driving architecture forums with repeatable methods.

Qualifications

• Bachelor's degree in Computer Science, Software Engineering, Information Systems, or a related field.
• Seven or more years of relevant experience in technology governance, architecture review, or platform engineering within a large enterprise environment.
• Proficiency in Python and experience building production-quality automation, evaluation pipelines, or workflow services.
• Experience designing and building knowledge bases and RAG solutions, including chunking strategies, embeddings, semantic retrieval, and grounded response generation.
• Working knowledge of vector search and storage technologies (OpenSearch, Pinecone) and large language model platforms (Amazon Bedrock, Azure OpenAI).
• Understanding of the applied AI lifecycle, including prompt design, evaluation, and output governance for document processing use cases.
• Knowledge of enterprise content and document management concepts (capture, metadata management, lifecycle governance, retention, search).
• Experience with cloud services used for document intelligence workflows (object storage, event streaming, document extraction).
• Ability to apply structured, rubric-based evaluation methods and explain recommendations in governance forums.
• Ability to write clear capability descriptions, assessment reports, and decision documentation for architecture audiences.

Responsibilities

• Serve as the document management domain intelligence lead, owning technology preferences and decision guidance for the domain.
• Evaluate inbound technology requests (vendor, open-source, internal), map requests to existing capabilities, and route items for review when needed.
• Maintain and improve the domain capability taxonomy, ensuring capabilities are current, clearly described, and consistently classified.
• Identify capability gaps between platform offerings and engineering demand, and translate gaps into inputs for the platform roadmap.
• Apply a rubric-based assessment method consistently, producing documented, defensible recommendations and decision records.
• Design and maintain a governed, queryable knowledge base covering capability definitions, assessment history, decision records, and platform non-functional requirements.
• Implement RAG pipelines over authoritative documentation to deliver accurate, citation-backed responses for engineers and stakeholders.
• Develop agentic evaluation workflows that retrieve relevant capabilities and prior assessments, draft preliminary recommendations, and score requests against the rubric.
• Build and maintain natural-language query experiences that help users understand capabilities, preferences, and outcomes with governed responses.
• Instrument governance and assessment workflows with measurable metrics and publish reporting for governance stakeholders.
• Create proofs of concept when needed to validate assessments and demonstrate alignment to existing services or need for new capability investment.

Skills

Python

Automation tooling

Evaluation pipelines

Workflow services

Knowledge bases

RAG solutions

Vector search

LLM platforms

Education

Bachelor's degree in CS/SE/IS

Tools

OpenSearch

Pinecone

Amazon Bedrock

Azure OpenAI

Job description

Help shape how enterprise document management technology is evaluated, adopted, and governed at scale. In this role, you will build practical artificial intelligence tooling that makes governance faster, more consistent, and evidence-based. You will partner closely with platform engineers and architecture stakeholders to improve decision quality and reuse across the organization. Your work will directly influence platform standards, capability definitions, and technology assessments.

As a Vice President Domain Intelligence Engineer in Document Management Platform, you own day-to-day domain governance and build intelligent tooling that scales how document management technologies are assessed and guided. You evaluate inbound technology requests, maintain the domain capability taxonomy, and identify gaps between demand and platform capabilities. You design and maintain a governed knowledge base and build Retrieval-Augmented Generation (RAG) and agentic workflows that accelerate assessments with documented, traceable outputs. You communicate recommendations clearly and support architecture forums with consistent, repeatable evaluation methods.

Within the first 90 days, you will align key platform initiatives to documented capabilities, complete initial technology assessments using the standard rubric, and publish an initial knowledge base for platform engineering users. Within six months, you will deliver an automated triage workflow that matches requests to capabilities and produces draft, rubric-based recommendations to reduce turnaround time. Within 12 months, you will establish the knowledge base as the trusted reference for domain decisions and keep the capability taxonomy current and defensible for architecture and information security stakeholders.

Job responsibilities

• Serve as the document management domain intelligence lead, owning technology preferences and decision guidance for the domain.
• Evaluate inbound technology requests (vendor, open-source, and internally developed), map requests to existing capabilities, and route items for further review when needed.
• Maintain and improve the domain capability taxonomy, ensuring capabilities are current, clearly described, and consistently classified.
• Identify capability gaps between platform offerings and engineering demand, and translate gaps into structured inputs for the platform roadmap.
• Apply a rubric-based assessment method consistently, producing documented, defensible recommendations and decision records.
• Design and maintain a governed, queryable knowledge base covering capability definitions, assessment history, decision records, and platform non-functional requirements.
• Implement RAG pipelines over authoritative documentation to deliver accurate, citation-backed responses for engineers and stakeholders.
• Develop agentic evaluation workflows that retrieve relevant capabilities and prior assessments, draft preliminary recommendations, and score requests against the rubric.
• Build and maintain natural-language query experiences that help users understand capabilities, preferences, and outcomes with governed responses.
• Instrument governance and assessment workflows with measurable metrics (for example, throughput, coverage, and taxonomy drift) and publish reporting for governance stakeholders.
• Create proofs of concept when needed to validate assessments and demonstrate whether requests align to existing services or require new capability investment.

Required qualifications, capabilities, and skills

• Bachelor's degree in Computer Science, Software Engineering, Information Systems, or a related field.
• Seven or more years of relevant experience in technology governance, architecture review, or platform engineering within a large enterprise environment.
• Proficiency in Python and experience building production-quality automation, evaluation pipelines, or workflow services.
• Experience designing and building knowledge bases and RAG solutions, including chunking strategies, embeddings, semantic retrieval, and grounded response generation.
• Working knowledge of vector search and storage technologies (for example, OpenSearch or Pinecone) and large language model platforms (for example, Amazon Bedrock or Azure OpenAI).
• Understanding of the applied artificial intelligence lifecycle, including prompt design, evaluation, and output governance for document processing use cases.
• Knowledge of enterprise content and document management concepts, such as capture, metadata management, lifecycle governance, retention, and search.
• Experience with cloud services used for document intelligence workflows (for example, object storage, event streaming, and document extraction services).
• Ability to apply structured, rubric-based evaluation methods and explain recommendations in governance forums.
• Ability to write clear capability descriptions, assessment reports, and decision documentation for architecture audiences.
• Demonstrated ability to manage competing priorities and deliver hig