Semantic Data and AI Engineer
Enterprise Knowledge
Job Overview
Location
Remote
Salary
USD 150,000 - 210,000 yearly
Employment Type
Full-time
Work Arrangement
Remote
Sector
Data & Analytics
Experience Level
Senior (5-8 years)
Application Deadline
June 3, 2026
About the Company
Enterprise Knowledge, LLC is a distinguished consulting firm dedicated to empowering organizations to effectively capture, manage, present, and leverage their information assets. Operating globally across both public and private sectors, EK focuses on maximizing the potential of people and information through end-to-end knowledge, data, content, and learning management consulting services.
The firm specializes in delivering practical solutions designed to ensure that an organization's knowledge, information, and data are easily discoverable, usable, and reusable, thereby driving maximum returns and enhancing customer and employee satisfaction. EK guides clients through digital, KM, or data transformations, with a particular emphasis on harnessing the power of semantic layers and knowledge graphs to realize Enterprise AI capabilities.
Their service offerings span a comprehensive range, from initial training and workshops to "Prove It" pilot projects and full-scale enterprise transformations. Enterprise Knowledge takes immense pride in its workplace culture, consistently recognized for its commitment to equity and inclusion, and has been honored on Inc. Magazine's list of Best Workplaces for five consecutive years (2018-2023).
Job Description
The field of enterprise knowledge management is rapidly evolving, driven by advancements in AI and semantic technologies. This role is pivotal in shaping the future of data discovery and integration within organizations.
You will leverage cutting-edge techniques in Natural Language Processing (NLP), including entity extraction and text classification, to transform raw data into actionable insights. Expertise in designing and deploying Retrieval-Augmented Generation (RAG) workflows and agentic AI solutions is crucial for driving business ROI and scaling organizational growth.
Your work will directly impact how businesses harness their knowledge assets for strategic decision-making and AI-driven transformations. The company fosters a collaborative environment and offers unique benefits, encouraging innovation and professional development.
To apply for this role, click the Apply button on this page and follow the instructions.
Required Skills
Key Responsibilities
- Work with data subject matter experts and business users to effectively understand and model their domain of knowledge
- Apply NLP techniques (entity extraction, classification, and document processing) to transform raw data and content into AI-ready assets
- Design, implement, test, and operate end-to-end RAG workflows for client engagements, including retrieval pipeline architecture, embedding strategies, and response evaluation
- Contribute to agentic AI solution design and implementation, including orchestration patterns, tool use, and memory and retrieval integration
- Support a variety of business intelligence projects using AI-based solutions
- Analyze complex datasets and communicate insights to both technical and non-technical stakeholders
- Design and implement data pipelines for ingesting, processing, and enriching structured and unstructured content using SQL, Python, R, or equivalent languages
- Contribute to semantic layer and knowledge graph implementations as part of larger AI solution architectures
- Work with internal and external teams to contextualize data engineering work into larger project context
Qualifications
- Bachelor’s degree in math, statistics, economics, data science, computer science, or a related field
- 5+ years experience working on data analysis project(s) designing reports and designing data analysis approaches and visualizations in a production setting
- Proven experience working directly with clients, providing briefings, facilitating meetings, and presenting work products
- Experience applying machine learning methods and statistical analysis to business use cases
- Proficiency in programming languages such as Python, R, or similar for data analysis and modeling
- Experience with NLP methods: entity extraction, text classification, document processing, or similar techniques applied to unstructured data in a production setting
- Hands-on experience building and optimizing RAG pipelines, including embedding strategies, reranking, and cross-encoder models
- Familiarity with retrieval quality and evaluation metrics (precision, recall, MRR, and user-centric evaluation approaches)
- Experience implementing monitoring and observability for RAG and AI components, including latency, success rate, cache hit rate, retrieval quality, and data drift
- Familiarity with data modeling, database architecture, and data integration, aggregation and normalization across heterogeneous sources
- Interest in developing as a consultant and taking on additional responsibilities for delivering and growing work
- Experience designing and working with relational databases
- Experience designing and working with graph databases and SPARQL
- Experience with AI governance practices covering model monitoring, evaluation frameworks, and access entitlements
- Comfortable working with containerized environments; Docker proficiency expected, Kubernetes familiarity a plus
- Experience with cloud platforms (AWS, Azure, or GCP) for deploying and operating AI and data solutions
- Exposure to ontology or taxonomy design, and familiarity with taxonomy/ontology management tools (Progress Semaphore, PoolParty, Synaptica, Mondeca, etc.)
- Experience designing and planning data science projects to meet business requirements
- Experience implementing agentic AI workflows using frameworks such as LangChain, LlamaIndex, LangGraph, BAML, or equivalent
How to Apply
To apply for this role, click the Apply button on this page and follow the instructions.
Join Our Communities
The field of enterprise knowledge management is rapidly evolving, driven by advancements in AI and semantic technologies. This role is pivotal in shaping the future of data discovery and integration within organizations. You will leverage cutting-edge techniques in Natural Language Processing (NLP), including entity extraction and text classification, to transform raw data into actionable insights. Expertise in designing and deploying Retrieval-Augmented Generation (RAG) workflows and agentic AI solutions is crucial for driving business ROI and scaling organizational growth. Your work will directly impact how businesses harness their knowledge assets for strategic decision-making and AI-driven transformations.
Posted Date
May 20, 2026