Full Stack AI Developer

Enterprise Knowledge•Arlington, VA

19h•Hybrid

About The Position

Enterprise Knowledge (EK) is hiring a full-time Full Stack AI Developer to join our growing Technology Solutions team. In this role, you will bridge the gap between robust software engineering and cutting-edge Generative AI, designing and deploying end-to-end solutions that transform how global organizations interact with their data. As a Full Stack AI Developer, you will be part of a team working on innovative projects, ranging from intelligent search interfaces to complex agentic AI systems that automate intricate business workflows. We are seeking a proactive, independent thinker with a passion for building functional, user-centric AI applications. As an EKer, you will join a fast-growing company that is committed to equity and inclusion, have the opportunity to work in a collaborative workplace, take advantage of our unique benefits, and help build our innovative culture. To read more about the impactful work we are doing and to see the latest thought leadership from EK, follow us on LinkedIn. Applicants must be currently authorized to work in the United States on a full-time basis. Enterprise Knowledge will not sponsor applicants for work visas.

Requirements

Bachelor’s degree in Computer Science, Data Science, Math, or a related technical field
1–3 years of professional software development experience, with a focus on both backend and frontend technologies
Proven experience building and optimizing RAG pipelines (embeddings, reranking, and evaluation) and applying Natural Language Processing (NLP) techniques to unstructured data
Proficiency in Python (preferred) or Java for backend development, and experience with modern JavaScript frameworks (e.g., React, TypeScript)
Familiarity with data modeling, database architecture, and SQL
Experience with code versioning tools (Git) and delivering solutions using Agile delivery practices
Proficiency in using Generative AI tools to accelerate the full Software Development Life Cycle (SDLC). This includes leveraging AI for generating Architecture Decision Records (ADRs), drafting code, creating comprehensive test cases, and producing product documentation
Strong ability to facilitate meetings, provide briefings, and present work products directly to clients

Nice To Haves

Hands-on experience implementing agentic AI workflows using frameworks such as LangChain, LangGraph, LlamaIndex, or BAML
Experience with RDF graph databases, SPARQL, or Linked Data technologies
Comfort working with containerized environments (Docker) and cloud platforms (AWS, Azure, or GCP) for deploying AI solutions
Experience implementing monitoring for AI components, including latency, success rate, and retrieval quality
Exposure to ontology/taxonomy design or management tools (e.g., Progress Semaphore, PoolParty)

Responsibilities

Design, implement, and maintain scalable backend microservices (Python) and intuitive frontend interfaces (React/Vue) for AI-driven applications
Contribute to the design and implementation of agentic AI solutions, including orchestration patterns, tool use, and memory/retrieval integration
Design and operate end-to-end Retrieval Augmented Generation (RAG) workflows, including retrieval pipeline architecture, embedding strategies, and response evaluation
Build and optimize data pipelines for ingesting and enriching structured and unstructured content using SQL and Python
Work with internal teams to integrate AI components with semantic layers and knowledge graph implementations
Develop middleware integration layers for decoupled systems, including content auto-tagging and seamless search experiences
Work with data subject matter experts and business users to understand their domain and communicate technical insights to non-technical stakeholders