Senior AI Developer

Select Source Solutions•Greenbelt, MD

4d•Remote

About The Position

Our client is seeking a remote Senior AI Developer to design, build, and integrate production artificial-intelligence solutions within modern cloud environments. This is a hands-on development role focused on moving AI beyond prototypes and into reliable applications and workflows. The Senior AI Developer will build solutions involving generative AI, large language models, retrieval-augmented generation, AI agents, APIs, knowledge systems, and cloud-based AI services. The right person combines strong software-engineering fundamentals with practical AI/ML experience. You should understand how to connect models with enterprise data and applications, build secure APIs and workflows around them, evaluate output quality, and deploy AI capabilities that can be reliably operated in production.

Requirements

7+ years of professional software engineering, data engineering, AI/ML engineering, or related technical experience.
Hands-on experience developing and deploying AI or machine-learning solutions into production environments.
Strong programming experience with Python.
Hands-on experience developing applications using large language models and generative AI.
Experience developing RAG, semantic-search, knowledge-retrieval, or comparable LLM-based solutions.
Experience developing APIs and integrating AI capabilities with external systems and data sources.
Experience using cloud-based AI or machine-learning services within AWS, Azure, GCP, or comparable environments.
Strong understanding of modern software-development, testing, source-control, and deployment practices.
Experience evaluating and improving AI application performance and output quality.
Must be able to hold a security clearance.

Nice To Haves

Experience developing agentic AI or multi-step AI workflows.
Experience with frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or comparable technologies.
Experience with Amazon Bedrock, SageMaker, Azure OpenAI, Azure AI Foundry, Vertex AI, or comparable cloud AI services.
Experience working with vector databases or vector-search technologies.
Experience integrating AI solutions with enterprise document and knowledge repositories.
Experience with Docker, Kubernetes, and cloud-native application deployment.
Experience with CI/CD and MLOps or LLMOps practices.
Experience implementing AI within federal, regulated, scientific, or mission-critical environments.

Responsibilities

Design, develop, test, and deploy production AI and machine-learning solutions.
Build generative AI and LLM-enabled applications using commercial, open-source, and cloud-based models.
Develop Retrieval-Augmented Generation (RAG) solutions that connect LLMs with enterprise or domain-specific knowledge sources.
Build AI agents and agentic workflows capable of interacting with applications, tools, APIs, and enterprise data.
Develop APIs and backend services that integrate AI capabilities into applications and business workflows.
Implement prompt-management, model-orchestration, retrieval, tool-use, and workflow logic.
Integrate AI solutions with databases, document repositories, vector stores, APIs, and other enterprise systems.
Design and implement document ingestion, chunking, embedding, indexing, search, and retrieval workflows.
Evaluate model and application performance, including accuracy, relevance, reliability, latency, and output quality.
Develop safeguards, validation, logging, monitoring, and other controls required to operate AI solutions reliably.
Deploy AI workloads into scalable cloud environments.
Work with cloud architects, software engineers, data engineers, cybersecurity teams, and business stakeholders.
Research and evaluate emerging AI models, tools, frameworks, and development approaches.
Build reusable components and patterns that accelerate future AI development.