AI Developer

M1 Technology•Chantilly, VA

About The Position

We are seeking a highly skilled AI Developer to design, build, and integrate AI capabilities within an enterprise AI Governance Platform. This role focuses on developing intelligent systems that support explainability, auditability, retrieval quality, and model performance monitoring in high-stakes environments. The ideal candidate will work closely with engineering, data, and domain experts to implement AI/ML solutions that are not only performant, but also transparent, traceable, and aligned with governance and compliance requirements. Clearance Requirement : TS/SCI with Polygraph

Requirements

5 to 7+ years of experience in AI/ML development or applied machine learning
Strong programming skills in Python (or similar languages) and experience with ML frameworks (e.g., PyTorch, TensorFlow)
Experience building and deploying machine learning models in production environments
Experience with natural language processing (NLP), large language models, or retrieval systems
Familiarity with vector databases and embedding models
Experience with cloud platforms such as AWS or Azure for ML workloads
Understanding of model evaluation, validation, and performance metrics
Experience working with APIs and integrating AI services into applications
Familiarity with Agile/Scrum development environments

Nice To Haves

Experience with large language model (LLM) integration and prompt engineering
Familiarity with explainable AI (XAI) techniques and model interpretability methods
Experience with retrieval-augmented generation (RAG) architectures
Knowledge of data governance, model governance, or AI compliance frameworks
Experience with distributed data processing tools (e.g., Spark)
Familiarity with containerization (Docker, Kubernetes) for ML deployment
Experience with monitoring tools for model performance and drift detection

Responsibilities

Collaborate with Chief Engineer, data scientists, and platform teams to translate AI governance requirements into technical solutions
Design, develop, and deploy machine learning and AI models to support reasoning, retrieval, and classification tasks
Build and maintain retrieval-augmented generation (RAG) pipelines and embedding-based search systems
Implement model evaluation frameworks, including performance tracking, calibration, and quality scoring
Develop systems for AI explainability, reasoning trace capture, and auditability
Integrate AI components into scalable APIs and microservices within a cloud-native architecture
Monitor model performance, drift, and data quality across production environments
Work with large datasets to build and maintain training, validation, and ground truth pipelines
Optimize AI systems for latency, scalability, and cost efficiency
Participate in Agile/Scrum ceremonies and contribute to iterative delivery