AI Developer IV

About the Opportunity

The AI Developer IV will join the Product and Services team as a senior, hands-on developer, designing, building, and integrating production AI solutions, including generative and agentic AI, LLM integrations, RAG and knowledge solutions, APIs, and cloud-based AI services in a remote work arrangement. This role writes production code and takes solutions from design through deployment, turning AI capabilities into reliable, scalable systems that teams and end users can depend on. The ideal candidate brings hands-on expertise in generative AI, LLM integration, and cloud-based AI services, along with the ability to translate emerging AI capabilities into practical, well-engineered solutions.

Success in this role means delivering production-grade AI solutions that run reliably and perform well in real-world use, serving as a trusted partner to stakeholders and users by turning AI ideas into working systems, and strengthening the team's engineering standards through high-quality code, thorough reviews, and sound development practices.

What You Will Do in This Role

The AI Developer IV designs, builds, and deploys production generative and agentic AI solutions, including LLM integrations, RAG pipelines, APIs, and cloud-based AI services, for federal scientific and environmental programs, applying responsible AI practices, monitoring, and continuous quality improvement while collaborating with stakeholders and writing clean, tested code.

Responsibilities include:

• Design, build, and deploy production AI solutions, including generative and agentic AI applications

• Integrate large language models (LLMs) into applications and workflows through APIs and SDKs

• Build RAG and knowledge solutions, including data ingestion, chunking, embeddings, vector search, and retrieval pipelines

• Develop agentic workflows that use tools, orchestration, and multi-step reasoning

• Build and maintain APIs and services that expose AI capabilities to internal teams and downstream systems

• Build AI-driven analytics and automation that improve operational visibility, reporting, and decision-making for federal programs

• Apply AI and LLM solutions to scientific and environmental data, including knowledge retrieval across technical and mission documentation

• Implement responsible AI practices, including human oversight, output validation, and auditability

• Deploy and operate AI services in the cloud using infrastructure as code and CI/CD practices

• Evaluate and improve AI solution quality, including accuracy, latency, cost, and reliability

• Implement monitoring, logging, and guardrails to keep AI systems observable, safe, and trustworthy

• Collaborate with architects, data teams, and stakeholders to translate requirements into working solutions

• Write clean, tested, well-documented code and participate in code reviews

• Perform other duties and responsibilities as assigned.

What You Will Bring

Basic Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience
• 8+ years of professional software development experience, including deploying solutions to production
• Strong proficiency in Python
• Hands-on experience building solutions with LLMs and generative AI (e.g., prompt design, function/tool calling, structured outputs)
• Experience building AI solutions in federal or other regulated environments, with attention to data security, privacy, and compliance (e.g., NIST, FedRAMP)
• Experience building RAG or knowledge-based solutions, including embeddings and vector databases
• Experience building APIs and services (e.g., FastAPI, Flask)
• Hands-on experience deploying applications and AI services in a major cloud environment (AWS, Azure, or GCP)
• Experience with CI/CD tooling and infrastructure as code
• Solid software development fundamentals: testing, version control (Git), code review, and documentation
• Strong communication skills and the ability to collaborate in a cross-functional environment

Preferred Qualifications

• Experience building agentic AI systems with frameworks such as LangChain, LlamaIndex, or similar
• Experience with cloud AI platforms and managed model services (e.g., AWS Bedrock, Azure OpenAI, Vertex AI)
• Experience evaluating and monitoring LLM applications
• Experience with AWS AI services such as Amazon Bedrock and SageMaker
• Experience applying AI to scientific, geospatial, or Earth observation data
• Experience with containerization (Docker) and container orchestration
• Familiarity with classical ML techniques and frameworks (e.g., scikit-learn, PyTorch)
• Cloud or AI/ML certification

Work authorization/security clearance requirements

• Ability to obtain a security clearance.

Work Environment

• This work is normally completed in a remote environment.

Physical Demands

• Prolonged periods of sitting at a desk and working on a computer.
• Must be able to access and navigate each department at the organization's and client facilities.

Travel Required

• No

Proficiency Requirement

• The employee is expected to demonstrate proficiency in all essential job functions, tools, and processes related to this position within the first 90 days of employment. This includes acquiring a thorough understanding of job-specific responsibilities, systems, and workflows as outlined during onboarding and training. Failure to meet this requirement may result in additional training, reassessment, or other actions as deemed necessary by management.