Full Stack AI Developer

Enterprise Knowledge, LLC

. Design, implement, and maintain scalable Python backend microservices and intuitive React/Vue frontend interfaces for AI-driven applications .

Posted 10/10/2026full-timeArlington • Virginia • United StatesJuniorMid-Level💰 $95,000 - $115,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and implementing scalable Python backend microservices and React/Vue frontend interfaces, with a strong focus on AI-driven applications and Retrieval Augmented Generation workflows. Proficient in collaborating with stakeholders to deliver technical solutions and optimize data pipelines.

Highest-signal resume keywords

Python Backend DevelopmentReact Frontend DevelopmentRetrieval Augmented Generation (RAG) PipelinesNatural Language Processing (NLP)Agile Delivery Practices

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

PythonJavaSQLData ModelingDatabase ArchitectureGenerative AI ToolsEmbedding StrategiesMiddleware IntegrationContent Auto-TaggingRDF Graph Databases

Soft Skills

CommunicationCollaborationFacilitationPresentation

Tools & Technologies

ReactTypeScriptGitDockerAWSAzureGCPLangChainLangGraphLlamaIndex

Certifications & Qualifications

Bachelor's Degree in Computer ScienceBachelor's Degree in Data ScienceBachelor's Degree in Math

Industry Keywords

AI-Driven ApplicationsSemantic LayersKnowledge Graph ImplementationsOntology DesignTaxonomy Management

Tech Stack

Tools & technologies

AWSAzureDockerGoogle Cloud PlatformJavaJavaScriptMicroservicesPythonReactSDLCSQLTypeScriptVue.js

About the role

Key responsibilities & impact

Design, implement, and maintain scalable Python backend microservices and intuitive React/Vue frontend interfaces for AI-driven applications
Contribute to agentic AI solutions involving 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 SQL and Python data pipelines for ingesting and enriching structured and unstructured content
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
Collaborate with data subject matter experts and business users to understand their domains
Communicate technical insights to non-technical stakeholders

Requirements

What you’ll need

Must live within a comfortable, commutable distance of the Arlington, Virginia office
Willingness to work on-site 3 days a week
Bachelor's degree in Computer Science, Data Science, Math, or a related technical field
2–5 years of professional software development experience focused on backend and frontend technologies
Proven experience building and optimizing RAG pipelines, including embeddings, reranking, and evaluation
Experience applying Natural Language Processing (NLP) techniques to unstructured data
Proficiency in Python or Java for backend development
Experience with modern JavaScript frameworks such as React and TypeScript
Familiarity with data modeling, database architecture, and SQL
Experience with Git
Experience delivering solutions using Agile delivery practices
Proficiency using Generative AI tools across the full Software Development Life Cycle, including generating Architecture Decision Records, drafting code, creating test cases, and producing product documentation
Ability to facilitate meetings, provide briefings, and present work products directly to clients
Enterprise Knowledge will not sponsor a new applicant for employment authorization or provide immigration-related support for this position
Preferred: hands-on experience with LangChain, LangGraph, LlamaIndex, or BAML
Preferred: experience with RDF graph databases, SPARQL, or Linked Data technologies
Preferred: experience with Docker and AWS, Azure, or GCP
Preferred: experience monitoring AI components, including latency, success rate, and retrieval quality
Preferred: exposure to ontology/taxonomy design or management tools such as Progress Semaphore or PoolParty

Benefits

Comp & perks

Collaborative workplace
Equity and inclusion commitment
Unique company benefits (specific benefits not itemized in the posting)