AI Developer IV, Scientific and Environmental Programs (Remote)

Select Source Solutions; United States; Remote; USD 140,000 - 190,000; Full time

Job summary

Select Source Solutions in the United States is seeking an AI Developer IV to join the Product and Services team in a remote capacity. You will build production AI solutions for federal scientific and environmental programs using geospatial data, LLMs, RAG, and APIs.

The role emphasizes accuracy, provenance, and reproducibility while collaborating with scientists and engineers. Ideal candidates bring 8+ years of software development, strong Python, and hands-on experience with cloud AI

Qualifications

• 8+ years of professional software development experience including production deployments.
• Experience with scientific, geospatial, environmental, or Earth observation data.
• Collaboration with scientists, researchers, or domain experts.
• Strong Python proficiency and scientific stack (NumPy, pandas, xarray).
• Hands-on experience with LLMs and generative AI, prompts and tooling.
• Experience building RAG/knowledge-based solutions with embeddings and vectors.
• Experience APIs and cloud deployments (AWS/Azure/GCP).
• CI/CD and infrastructure as code; testing, Git, docs.
• Strong cross-functional communication and teamwork.

Responsibilities

• Design, build, and deploy production AI solutions for federal programs.
• Apply LLM and generative AI to scientific and geospatial data.
• Build RAG and knowledge retrieval across technical docs and data.
• Collaborate with scientists to translate research questions into AI systems.
• Validate AI outputs against scientific standards (accuracy, provenance).
• Develop agentic workflows with tools and orchestration.
• Integrate LLMs into applications via APIs/SDKs.
• Build and maintain APIs and services exposing AI capabilities.
• Write clean, tested code and participate in reviews.
• Deploy AI services in the cloud using IaC and CI/CD.

Skills

Python

NumPy

pandas

xarray

LLMs

RAG

APIs

FastAPI

AWS

CI/CD

Git

Communication

Education

Bachelor's degree in Computer Science or related field

Advanced degree in scientific discipline

Tools

Docker

Kubernetes

LangChain

LlamaIndex

AWS Bedrock

SageMaker

Terraform

FastAPI

Job description

AI Developer IV, Scientific and Environmental Programs (Remote)

About the Opportunity
The AI Developer IV will join the Product and Services team as a senior, hands-on developer building production AI solutions for federal scientific and environmental programs in a remote work arrangement. This is not a general AI role. You will work directly with scientific and Earth observation data, technical mission documentation, and the researchers and program teams who depend on it. The work spans generative and agentic AI, LLM integrations, RAG and knowledge solutions, APIs, and cloud-based AI services, but the measure of success is whether those systems produce results scientists can trust.

The ideal candidate combines strong production engineering skills with real experience working alongside scientific data. You understand how scientific datasets are structured, where they break, and why accuracy and provenance matter more than a polished demo.

Success in this role means delivering AI solutions that hold up to scientific scrutiny, earning the trust of domain experts by speaking their language, and strengthening the team's engineering standards through high-quality code, thorough reviews, and sound development practices.

What You Will Do in This Role

• Design, build, and deploy production AI solutions that support federal scientific and environmental programs
• Apply LLM and generative AI solutions to scientific, geospatial, and Earth observation data
• Build RAG and knowledge retrieval solutions across technical, scientific, and mission documentation, including data ingestion, chunking, embeddings, vector search, and retrieval pipelines
• Work with scientists and subject matter experts to understand research questions and translate them into working AI systems
• Validate AI outputs against scientific standards, with attention to accuracy, provenance, uncertainty, and reproducibility
• Develop agentic workflows that use tools, orchestration, and multi-step reasoning to support analysis and research tasks
• Integrate LLMs into applications and workflows through APIs and SDKs
• 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
• 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
• 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, a physical, environmental, or Earth science, or a related field, or equivalent practical experience
• 8+ years of professional software development experience, including deploying solutions to production
• Demonstrated experience working with scientific, geospatial, environmental, or Earth observation data in a professional or research setting
• Experience collaborating directly with scientists, researchers, or technical domain experts
• Strong proficiency in Python, including the scientific Python ecosystem (e.g., NumPy, pandas, xarray)
• Hands-on experience building solutions with LLMs and generative AI (e.g., prompt design, function/tool calling, structured outputs)
• Experience building RAG or knowledge-based solutions, including embeddings and vector databases
• Experience building AI solutions in federal or other regulated environments, with attention to data security, privacy, and compliance (e.g., NIST, FedRAMP)
• 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

• Advanced degree or research background in a scientific discipline
• Experience with common scientific and geospatial data formats (e.g., NetCDF, HDF5, GeoTIFF) and geospatial tools
• Experience supporting federal science, research, or environmental missions
• Familiarity with classical ML techniques and frameworks (e.g., scikit-learn, PyTorch), particularly as applied to scientific data
• 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 with AWS AI services such as Amazon Bedrock and SageMaker
• Experience evaluating and monitoring LLM applications
• Experience with containerization (Docker) and container orchestration
• 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.