AI Engineer, Associate
LCG, Inc.
•
Bethesda, MD
0
0
0
0
Not Applicable
Posted April 5, 2026
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Responsibilities
Commitments
Responsibilities
- AI Solutions Development
- 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
- 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 Cloud Engineering and AI Infrastructure
- 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.
- Full Stack Development and Integration
- 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.
- AI Use Case Development and Pilot Implementation
- 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.
- Testing, Documentation, and Testing
- 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 a 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.
Commitments
Sponsorship: No sponsorship assistance is available for this position.
Duration: 7 Months (May 2026 - December 2026)
Hybrid: Minimum of 2 Days Onsite (May increase as Client needs may increase)
Not Met Priorities
What still needs stronger evidence
Requirements
- Develop backend and automation services using Python, FastAPI, and modern API frameworks.
- AI Use Case Development and Pilot Implementation
- 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.
- Experience integrating LLM-based systems with enterprise applications and APIs.
- AI / Machine Learning certification
- Cloud architecture or DevOps certification
- 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
Preferred Skills
- Experience integrating LLM-based systems with enterprise applications and APIs.
- Experience supporting federal IT environments (NIH or HHS preferred) (nice to have)
- Experience implementing secure AI architectures in cloud environments.
- Certifications (Preferred)
- 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
Education
- (Not required) – Education - Bachelor’s degree from an accredited institution in related fields (Computer Science, Information Technology, Engineering, Mathematics, Data Science, Artificial Intelligence, etc)
- (Required) – Minimum 2 years of experience applying AI or machine learning to real-world technology solutions.
- (Not required) – Experience integrating LLM-based systems with enterprise applications and APIs.
- (Not required) – Experience supporting federal IT environments (NIH or HHS preferred) (nice to have)
- (Not required) – Experience implementing secure AI architectures in cloud environments.
- (Not required) – Microsoft Azure AI Engineer Associate
- (Not required) – Microsoft Azure Developer Associate
- (Not required) – Microsoft Azure Fundamentals (AZ-900)
- (Not required) – AI / Machine Learning certification
- (Not required) – Cloud architecture or DevOps certification
Job title: Full Stack Developer / AI Engineer, Associate
Location: Bethesda, MD
Clearance: Public Trust
Sponsorship: No sponsorship assistance is available for this position.
Duration: 7 Months (May 2026 - December 2026)
Hybrid: Minimum of 2 Days Onsite (May increase as Client needs may increase)
Job Overview: 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.
Key Responsibilities
AI Solutions Development
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
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 Cloud Engineering and AI Infrastructure
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. Full Stack Development and Integration
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.
AI Use Case Development and Pilot Implementation
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.
Testing, Documentation, and Testing
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 a 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.
Qualifications
Education - Bachelor’s degree from an accredited institution in related fields (Computer Science, Information Technology, Engineering, Mathematics, Data Science, Artificial Intelligence, etc)
Experience
Required:
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.
Preferred
Experience integrating LLM-based systems with enterprise applications and APIs.
Experience supporting federal IT environments (NIH or HHS preferred) (nice to have)
Experience implementing secure AI architectures in cloud environments.
Certifications (Preferred)
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
Required Skills And Competencies
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
Compensation And Benefits
The projected compensation range for this position is $90,000 to $110,000 per year benchmarked in the Washington, D.C. metropolitan area. The salary range provided is a good faith estimate representative of all experience levels. Salary at LCG is determined by various factors, including but not limited to role, location, the combination of education/training, knowledge, skills, competencies, certifications, and work experience.
LCG offers a competitive, comprehensive benefits package which includes health insurance options (medical, dental, vision), life and disability insurance, retirement plan contributions, as well as paid leave, federal holidays, professional development, and lifestyle benefits.
Devoted to Fair and Inclusive Practices
All qualified applicants will receive consideration for employment without regard to sex, race, ethnicity, age, national origin, citizenship, religion, physical or mental disability, medical condition, genetic information, pregnancy, family structure, marital status, ancestry, domestic partner status, sexual orientation, gender identity or expression, veteran or military status, or any other basis prohibited by law.
If you are interested in applying for employment with LCG and need special assistance or an accommodation to apply for a posted position, contact our Human Resources department by email at hr@lcginc.com.
Securing Your Data
Beware of fraudulent job offers using LCG's name. LCG will never request payment-related details or advancement of money during the application process. Legitimate communication will only come from lcginc.com or system@hirebridgemail.com emails, not free commercial services like Gmail or WhatsApp. If you receive suspicious emails asking for payment or personal information, contact us immediately at hr@lcginc.com.
If you believe you are the victim of a scam, contact your local law enforcement and report the incident to the U.S. Federal Trade Commission.
Location: Bethesda, MD
Clearance: Public Trust
Sponsorship: No sponsorship assistance is available for this position.
Duration: 7 Months (May 2026 - December 2026)
Hybrid: Minimum of 2 Days Onsite (May increase as Client needs may increase)
Job Overview: 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.
Key Responsibilities
AI Solutions Development
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
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 Cloud Engineering and AI Infrastructure
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. Full Stack Development and Integration
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.
AI Use Case Development and Pilot Implementation
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.
Testing, Documentation, and Testing
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 a 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.
Qualifications
Education - Bachelor’s degree from an accredited institution in related fields (Computer Science, Information Technology, Engineering, Mathematics, Data Science, Artificial Intelligence, etc)
Experience
Required:
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.
Preferred
Experience integrating LLM-based systems with enterprise applications and APIs.
Experience supporting federal IT environments (NIH or HHS preferred) (nice to have)
Experience implementing secure AI architectures in cloud environments.
Certifications (Preferred)
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
Required Skills And Competencies
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
Compensation And Benefits
The projected compensation range for this position is $90,000 to $110,000 per year benchmarked in the Washington, D.C. metropolitan area. The salary range provided is a good faith estimate representative of all experience levels. Salary at LCG is determined by various factors, including but not limited to role, location, the combination of education/training, knowledge, skills, competencies, certifications, and work experience.
LCG offers a competitive, comprehensive benefits package which includes health insurance options (medical, dental, vision), life and disability insurance, retirement plan contributions, as well as paid leave, federal holidays, professional development, and lifestyle benefits.
Devoted to Fair and Inclusive Practices
All qualified applicants will receive consideration for employment without regard to sex, race, ethnicity, age, national origin, citizenship, religion, physical or mental disability, medical condition, genetic information, pregnancy, family structure, marital status, ancestry, domestic partner status, sexual orientation, gender identity or expression, veteran or military status, or any other basis prohibited by law.
If you are interested in applying for employment with LCG and need special assistance or an accommodation to apply for a posted position, contact our Human Resources department by email at hr@lcginc.com.
Securing Your Data
Beware of fraudulent job offers using LCG's name. LCG will never request payment-related details or advancement of money during the application process. Legitimate communication will only come from lcginc.com or system@hirebridgemail.com emails, not free commercial services like Gmail or WhatsApp. If you receive suspicious emails asking for payment or personal information, contact us immediately at hr@lcginc.com.
If you believe you are the victim of a scam, contact your local law enforcement and report the incident to the U.S. Federal Trade Commission.