Position contingent on contract award - details below are subject to change based on final award.

In this role, you will define and deliver mission-critical AI-enabled web applications that address complex, high-impact client challenges. You will apply modern generative AI techniques to design and build retrieval-based knowledge assistants, chatbot experiences, and agentic workflows that integrate data processing, orchestration, and multi-agent components behind intuitive user interfaces. You will collaborate with enterprise and solutions architects, product owners, AI engineers, data engineers, and DevSecOps teams to deliver secure, scalable, and maintainable production solutions. Your technical expertise will help clients translate emerging AI capabilities into practical applications that improve how people access information, make decisions, and carry out their work.

Key Responsibilities:

• Build and enhance production generative AI applications and web-based AI solutions.
• Develop AI applications using Azure AI Foundry, Azure OpenAI, and Foundry Agent Service.
• Build retrieval-augmented generation (RAG) systems, knowledge assistants, chatbots, and agentic workflows.
• Implement agent and LLM workflows that use tools, structured outputs, guardrails, and human review where needed.
• Integrate AI applications with APIs, enterprise data sources, databases, cloud services, and MCP-based tools.
• Develop secure, cloud-native application services and user interfaces using Python, web frameworks, containers, and Azure services.
• Test, evaluate, and monitor AI applications to improve quality, reliability, latency, and cost.
• Work with AI engineers, software engineers, architects, and DevSecOps teams to deliver maintainable production applications.

• Must be currently located in Atlanta, GA or Washington, DC and able to work onsite when needed. 
• 5+ years of hands-on technical experience in software engineering, web application development, data engineering, data science, machine learning, or related technical discipline
• 1+ years of hands-on experience building generative AI or agentic AI solutions, including LLM APIs, prompt engineering, tool/function calling, structured outputs, retrieval-augmented generation (RAG), agents, or similar techniques
• Experience developing applications with Python and working with APIs, backend services, data pipelines, and web application frameworks
• Experience with REST APIs, JSON-based interfaces, authentication mechanisms, and external service integrations
• Experience with at least one major cloud platform, such as Microsoft Azure or AWS, including deploying or integrating applications with cloud-hosted services
• Experience using modern software-development practices and collaboration tools, such as Git, GitHub, Jira, pull requests, code reviews, issue tracking, and Agile/Scrum delivery practices
• Knowledge of LLM application fundamentals, including tokens, context windows, system and user prompts, model parameters, structured outputs, embeddings, retrieval, and techniques for guiding and evaluating model responses
• Ability to obtain and maintain a Public Trust or suitability determination, as required by the client or contract
• Bachelor’s degree in computer science, engineering, or a related field
• Must be a U.S. Citizen or Lawful Permanent Resident (Green Card Holder)

Preferred qualifications: 

• Experience with containerized or cloud-native application development, including Docker, Azure Container Apps, Azure App Service, or similar services
• Experience with Model Context Protocol (MCP) integrations and agent tool calling, including hands-on development of multi-agent systems
• Experience with implementing LLM evaluation, tracing, monitoring, and observability capabilities
• Experience with CI/CD, automated testing, and cloud-based development and deployment practices for AI applications
• Experience working in government, healthcare, or other regulated environments
• Exposure to fine-tuning, hosting, or serving open-source LLMs and working with model-serving frameworks
• Knowledge of AI governance, responsible AI principles, and related security and risk-management practices
• Knowledge of AI agent frameworks such as Microsoft Agent Framework, LangGraph, PydanticAI, or similar tools
• Ability to work effectively in a cross-functional engineering environment and collaborate with software, AI/ML, data, cloud, and DevSecOps engineers
• Ability to clearly communicate technical problems, implementation decisions, and trade-offs to both technical and non-technical stakeholders

Final salary determination based on skill-set, qualifications, and approved funding.

Many of our jobs come with great benefits – Some offerings are dependent upon the role, work schedule, or location, and may include the following:

Paid Time Off

            PTO / Vacation – 5.67 hours accrued per pay period / 136 hours accrued annually 

            Paid Holidays - 11

            California residents receive an additional 24 hours of sick leave a year

Health & Wellness

            Medical

            Dental

            Vision

            Prescription

            Employee Assistance Program

            Short- & Long-Term Disability

            Life and AD&D Insurance

Spending Account

            Flexible Spending Account

            Health Savings Account

            Health Reimbursement Account

            Dependent Care Spending Account

            Commuter Benefits

Retirement

            401k / 401a

Voluntary Benefits

            Hospital Indemnity

            Critical Illness

            Accident Insurance

            Pet Insurance

            Legal Insurance

            ID Theft Protection