Junior AI Developer

• Develop, test, and maintain software components for AI/ML pilot projects and use cases, including Google Gemini-based applications, AI agents, and tool/MCP integrations, under the direction of senior team members.
• Build and consume RESTful APIs and back-end services (e.g., Python with FastAPI or Flask) that connect applications to commercial or open-source AI models and enterprise data sources.
• Write and refine prompts, and help evaluate model outputs for accuracy, reliability, and consistency.
• Write unit tests and perform API testing (e.g., Postman) to validate request/response behavior, authentication flows, and error handling before release.
• Work with SQL and NoSQL data stores and cloud data services (e.g., Google BigQuery) to query, prepare, and serve data to AI-enabled applications.
• Support deployment of applications to cloud environments (Google Cloud and AWS) and through CI/CD pipelines.
• Use AI-assisted development tools responsibly to accelerate coding, testing, and documentation, in line with program policies.
• Collaborate with developers, testers, and Data Scientist teams on prototyping teams that deliver working software on short timelines.
• Actively participate in agile delivery ceremonies, including sprint planning, daily stand-ups, sprint testing, demonstrations, and retrospectives.
• Author clear technical documentation, including design notes, API documentation, and handoff/transition materials.
• Stay current with advancements in AI technologies, tools, and best practices, and share what you learn with the team.

You must live within the DC, MD, VA area.

U.S. Citizenship is required. Candidate must be able to obtain a CBP Public Trust clearance.

• Bachelor’s degree (B.A./B.S.) in Computer Science, Software Engineering, Data Science, or a related field, conferred by the start date.
• 0-2 years of professional software development experience; relevant internships, co-ops, research, and substantial academic or personal projects will be considered.
• Programming proficiency in Python plus at least one additional language such as Java, JavaScript, or TypeScript.
• Hands-on experience building or consuming RESTful APIs, including familiarity with authentication methods, data formats (JSON/YAML), and API error handling.
• Familiarity with fundamental Generative AI concepts, including Large Language Models (LLMs), prompt engineering, and agentic AI patterns.
• Exposure to building an application that integrates a commercial or open-source AI model API (academic, internship, or project experience acceptable).
• Working knowledge of SQL and exposure to at least one cloud platform (Google Cloud or AWS).
• Experience with Git-based version control, unit testing, and object-oriented programming.
• Exposure to Agile/Scrum development practices.
• Strong communication skills, willingness to learn, and the ability to take direction and work effectively on a collaborative team.

Preferred Skills and Experience:

• Experience with Google Gemini, Google Vertex AI, or AWS Bedrock.
• Experience building AI agents or agentic workflows, or working with the Model Context Protocol (MCP).
• Experience with Python web frameworks such as FastAPI or Flask.
• Experience with Google Cloud data services such as BigQuery, including awareness of query cost and performance.
• Coursework or project experience in machine learning (e.g., classification models, neural networks) or data science.
• Experience with a front-end framework such as React or Angular.
• Experience with NoSQL databases (e.g., MongoDB).
• Exposure to DevOps/DevSecOps and CI/CD tools such as GitLab.
• Entry-level technical certifications such as Google Cloud Digital Leader, AWS Certified Cloud Practitioner, or AWS Certified AI Practitioner.
• Experience working in a geographically dispersed, remote team.