Junior AI Developer

C Mack Solutions LLC•Ashburn, VA

18h

About The Position

C. Mack Solutions is seeking a Junior AI Developer to join an agile AI development team supporting a mission-critical Federal Government program. Working under the guidance of senior developers and architects, the successful candidate will help build, test, and integrate AI-enabled applications, including Generative AI and agentic solutions built on Google Gemini. The role offers mentorship, rapid iteration, and a focus on delivering working software. The developer will contribute to AI/ML pilot projects, create and consume APIs and back-end services, evaluate prompts and model outputs, work with data stores and cloud services, and support cloud deployment and CI/CD. The position also involves testing, documentation, collaboration with developers, testers, and data scientists, and participation in agile delivery ceremonies.

Requirements

Live within the DC, Maryland, or Virginia area.
U.S. citizenship; must be able to obtain a CBP Public Trust clearance.
Bachelor’s degree 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 are considered.
Programming proficiency in Python and at least one additional language, such as Java, JavaScript, or TypeScript.
Hands-on experience building or consuming RESTful APIs, including familiarity with authentication methods, JSON/YAML data formats, and API error handling.
Familiarity with Generative AI fundamentals, including 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 is 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 ability to take direction and work effectively on a collaborative team.

Nice To Haves

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, such as classification models or neural networks, or in data science.
Experience with a front-end framework such as React or Angular.
Experience with NoSQL databases such as 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.

Responsibilities

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 senior team members’ direction.
Build and consume RESTful APIs and back-end services, such as Python services using FastAPI or Flask, to connect applications to 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, such as with Postman, to validate request and response behavior, authentication flows, and error handling before release.
Work with SQL and NoSQL data stores and cloud data services, such as Google BigQuery, to query, prepare, and serve data to AI-enabled applications.
Support application deployment to Google Cloud and AWS environments 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 delivering working software on short timelines.
Participate in agile delivery ceremonies, including sprint planning, daily stand-ups, sprint testing, demonstrations, and retrospectives.
Author technical documentation, including design notes, API documentation, and handoff or transition materials.
Stay current with AI technologies, tools, and best practices and share learnings with the team.