Senior Full Stack Developer

Enterprise Knowledge•Arlington, VA

5h•$140,000 - $155,000•Hybrid

About The Position

Enterprise Knowledge (EK) is hiring a full-time Senior Full Stack Developer to join our growing Enterprise Delivery team. In this role, you will bridge the gap between robust software engineering and cutting-edge Generative AI, leading the design, implementation, and deployment of end-to-end solutions that transform how global organizations interact with their data. As a Senior Full Stack Developer, you will take a leading role on project teams, 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 who can own system design end-to-end and mentor junior engineers. Our forward-deployed developers work alongside business stakeholders and customer development teams to design, build, and implement solutions that meet critical business needs. 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.

Requirements

Bachelor's degree in Computer Science, Data Science, Math, or a related technical field
8+ years of professional software development experience, including demonstrated experience leading projects or workstreams and mentoring other engineers
Deep proficiency in Python (preferred), Golang, or Java for backend development, and extensive experience with modern JavaScript frameworks (e.g., React, TypeScript)
Strong background in data modeling, database architecture, and SQL, with experience making architectural tradeoffs at scale
Proven experience with code versioning tools (Git), CI/CD (GitHub Actions), and leading teams through Agile delivery practices
Proficiency in using Generative AI tools to accelerate the full Software Development Life Cycle (SDLC), including generating Architecture Decision Records (ADRs), drafting code, creating comprehensive test cases, and producing product documentation
Demonstrated ability to lead technical teams, facilitate client meetings, provide briefings, and present work products and solution designs directly to senior client stakeholders

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.
Deep comfort working with containerized environments (Docker) and cloud platforms (AWS, Azure, or GCP) for deploying AI solutions at scale
Experience designing and 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)
Proven track record designing, building, and optimizing RAG pipelines (embeddings, reranking, and evaluation) and applying Natural Language Processing (NLP) techniques to unstructured data
Prior experience in formally mentoring junior developers or leading small technical teams

Responsibilities

Lead development on client projects, setting technical direction, making architectural and system design decisions, and ensuring delivery quality across the team
Design, implement, and maintain scalable backend microservices (Python) and intuitive frontend interfaces (React/Vue) for AI-driven applications
Own the design of complex system components end-to-end and communicate that design clearly to both technical and non-technical clients
Mentor and coach junior and mid-level developers, conducting code reviews, providing technical guidance, and helping grow team capabilities
Design, maintain, and implement solutions that adhere to security, access controls, scalability, and other constraints informed by client requirements
Lead design and implementation of agentic AI solutions, including orchestration patterns, tool use, and memory/retrieval integration
Architect end-to-end Retrieval Augmented Generation (RAG) workflows, including retrieval pipeline architecture, embedding strategies, and response evaluation
Lead development of and optimize data pipelines for ingesting and enriching structured and unstructured content using SQL, Python, and other scripting or querying strategies
Lead development and configuration of CI/CD and various other DevOps processes that support scalable, continuously available, and maintainable system-centric deployment processes
Partner with internal teams to integrate AI components with semantic layers and knowledge graph implementations
Design, configure, and advise clientele on production-grade system security, access control (RBAC/ABAC), and network architecture (ingress/egress)
Lead design and development of middleware integration layers for decoupled systems, including content auto-tagging, semantic data contracts, and seamless search experiences
Serve as a trusted technical advisor to data subject matter experts and business users, translating complex technical concepts for non-technical stakeholders