AI Full Stack Developer, Mid

Booz Allen Hamilton•McLean, VA

3d•$69,400 - $158,000

About The Position

As an AI Full Stack Developer, you will design, develop, and deploy enterprise AI/ML solutions across the full application stack. You will collaborate with data scientists, software engineers, DevOps teams, and stakeholders to build user-facing applications, productionize machine learning models, optimize pipelines, and implement responsible AI practices. The role involves developing scalable AI/ML applications with modern frontend, backend, cloud, data, and machine learning technologies. You will contribute to secure, compliant, and maintainable solutions supporting experimentation, model deployment, monitoring, and enterprise operations. U.S. citizenship is required because of the nature of work performed at the facility. Applicants selected will be subject to a government investigation and must meet applicable U.S. government client eligibility requirements, including a Public Trust determination.

Requirements

At least 6 years of experience in full-stack software development.
At least 3 years of experience with AI/ML engineering.
Experience with Python and developing backend services, APIs, or data-processing applications leveraging Java.
Experience with frontend development using JavaScript or TypeScript and frameworks such as React, Angular, or Vue.
Experience designing and integrating REST or GraphQL APIs, microservices, and enterprise application integration.
Experience with machine learning frameworks such as TensorFlow, PyTorch, LangChain, OpenCV, OpenAI, AutoGen, CrewAI, or Scikit-learn.
Experience with cloud platforms such as AWS, Azure, or GCP, and with CI/CD and MLOps practices.
Experience working with relational databases and with NoSQL, vector database, or caching technologies.
Public Trust determination is required.
Bachelor’s degree in a Computer Science field.
U.S. citizenship is required.
Applicants must complete the required skills assessment and meet its minimum proficiency threshold to continue in the hiring process.

Nice To Haves

Experience with feature stores, model registries, or model-serving platforms.
Experience with containerization and orchestration technologies such as Docker and Kubernetes.
Experience with cloud-native application development and distributed systems.
Experience implementing OpenTelemetry or similar observability solutions.
Experience working in federal or other highly regulated environments.
Knowledge of vector databases such as Pinecone, Weaviate, FAISS, or similar technologies.
Knowledge of responsible AI frameworks, ethics, security, privacy, and compliance.
Ability to explore and learn new technologies.
Excellent collaboration and problem-solving skills.

Responsibilities

Design, develop, test, and maintain full-stack AI/ML applications and services.
Build frontend interfaces and user workflows for interacting with AI/ML capabilities.
Develop backend services, APIs, and integrations using Python and frameworks such as FastAPI, Flask, or similar technologies.
Build and manage AI/ML pipelines for experimentation, training, evaluation, and deployment.
Operationalize machine learning models in production environments, including containers, APIs, and cloud services.
Support development of a Model Control Plane (MCP) for model registry, deployment, versioning, and monitoring.
Integrate applications with relational databases, vector databases, feature stores, and distributed caching services.
Implement authentication, authorization, secure API practices, and data protection safeguards.
Develop automated tests across frontend, backend, API, data pipeline, and ML components.
Apply responsible AI principles, including human-in-the-loop workflows, content moderation, explainability, and data privacy safeguards.
Collaborate cross-functionally to ensure secure, compliant, maintainable, and scalable AI/ML deployments.