AI Developer / Full Stack Developer Associate

LCG, Inc.•Maryland, MD

3d•$90,000 - $110,000•Hybrid

About The Position

LCG is seeking a Full Stack Developer / AI Engineer – Associate to support our NIH client in developing innovative AI-powered solutions using Azure OpenAI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and modern full stack technologies. This role will support an NIH client that aims to design and implement AI-driven applications that automate and enhance internal NIH business processes. The developer will design and build Generative AI applications, chatbots, and intelligent automation tools to support use cases such as compliance review, policy analysis, meeting scheduling, grant monitoring, and research reporting. The successful candidate will support configuration and assist with optimizing secure Azure OpenAI cloud infrastructure, design LLM-integrated applications using Python-based APIs, and enhance the existing client AI Chat Tool to improve knowledge retrieval and operational efficiency. The role involves building React-based front-end interfaces, developing FastAPI services for AI integration, and implementing vector databases to support semantic search and RAG pipelines. This role will work closely with client leadership, technical teams, and pilot users to prototype, deploy, and refine AI capabilities while ensuring alignment with federal IT security, governance, and change management processes. This position offers an opportunity to contribute to cutting-edge AI modernization initiatives at NIH, helping federal programs leverage Generative AI technologies to improve efficiency, decision-making, and operational insights.

Requirements

Minimum 2 years of experience applying AI or machine learning to real-world technology solutions.
Minimum 2 years of experience working with Microsoft Azure Cloud and Azure OpenAI services.
Experience designing and implementing AI-powered applications using LLMs or Generative AI technologies.
Experience developing RAG pipelines, AI chatbots, or intelligent automation tools.
Strong programming skills in Python, with experience developing APIs using FastAPI or similar frameworks.
Experience building modern front-end interfaces using React or similar JavaScript frameworks.
Experience working with vector databases (Azure Databases) to support semantic search or AI retrieval workflows.
Experience with data engineering technologies including SQL, NoSQL, and API integrations.
Experience using GitHub for source code management, version control, pull requests, and collaborative development workflows.
Strong analytical thinking and problem-solving abilities
Ability to translate complex technical concepts to non-technical stakeholders
Excellent written and verbal communication skills
Ability to manage multiple priorities in a fast-paced environment
High attention to detail and commitment to quality
Work independently, Self-motivated, proactive, and highly organized

Nice To Haves

Experience integrating LLM-based systems with enterprise applications and APIs.
Experience supporting federal IT environments (NIH or HHS preferred)
Experience implementing secure AI architectures in cloud environments.
Microsoft Azure AI Engineer Associate
Microsoft Azure Developer Associate
Microsoft Azure Fundamentals (AZ-900)
ITIL 4
AI / Machine Learning certification
Cloud architecture or DevOps certification

Responsibilities

Develop and implement AI-powered applications using Azure OpenAI, LLM technologies, Retrieval-Augmented Generation (RAG) pipelines, and vector database architectures
Design and build Generative AI applications, intelligent agents, and chatbot solutions that automate internal business processes and support staff workflows.
Implement semantic search and document retrieval systems using vector databases to support AI-driven knowledge retrieval.
Enhance and maintain the existing client AI Chat Tool, improving user experience and response accuracy through AI technologies.
Develop intelligent Generative AI applications supporting use cases such as: Compliance verification for new policies and funding opportunities, Policy and regulatory change analysis, AI-driven meeting scheduling and coordination, Monitoring of grant and clinical trial activities, Knowledge retrieval from internal documentation and SOP repositories.
Support the configuration and enhancement of secure Azure cloud infrastructure used to host AI applications and services, including: Azure OpenAI services, Azure Storage accounts, Azure Applications and Database services.
Assist cloud and infrastructure teams with deploying AI-powered applications that leverage vector databases and RAG architectures.
Work within the existing Azure OpenAI environment to integrate AI services and ensure applications function effectively within the client’s cloud infrastructure.
Collaborate with cloud engineering and security teams to ensure AI solutions align with NIH cloud governance, security policies, and infrastructure standards.
Assist with documenting AI solution architecture and implementation components.
Develop full stack AI applications using React for front-end interfaces and Python-based APIs for backend services.
Build RESTful APIs and AI service endpoints using FastAPI to connect LLM services with enterprise applications.
Support development of RAG pipeline components integrating vector databases with enterprise data sources.
Assist in developing LLM-integrated applications and APIs that connect AI services with enterprise systems.
Implement data pipelines and integrations using SQL, NoSQL, and vector databases as well as external APIs.
Develop backend and automation services using Python, FastAPI, and modern API frameworks.
Utilize GitHub for version control, code collaboration, and maintaining source code repositories across development environments.
Collaborate with stakeholders to define, prototype, test, and deploy AI use cases.
Work with client staff to assess automation opportunities and evaluate operational efficiency improvements.
Support analysis of automation opportunities and document potential efficiency improvements.
Assist with analyzing and documenting cloud resource usage and cost considerations for AI deployments.
Leverage Microsoft Power Automate to support workflow automation and integrate AI-powered processes into existing business applications.
Utilize Power BI to develop dashboards and reports that visualize application performance, usage metrics, operational insights for stakeholders.
Prepare and complete status reports, providing updates on development progress, milestones, risks, and pilot outcomes to client leadership and stakeholders.
Conduct User Acceptance Testing (UAT) with pilot users and incorporate feedback into system improvements.
Develop technical documentation, including: Requirements documentation, Architecture and design documents, Testing plans and implementation strategies, Standard operating procedures (SOPs).
Create fact sheets for Generative AI applications developed, summarizing functionality, key features, use cases, and benefit for stakeholders and end users.
Develop training materials and recorded training sessions to support user adoption.