Looking for PURPOSE? At GovStar, we found it. We love the work we do, the people we do it with, and the impact we have. We’re looking for talented technologists and creatives with the character, courage, and commitment to achieve greatness and grow together. We’re a tight group of individuals coming together to produce Legendary Teams. We are using technology and creativity to unlock the future of government and shape a brighter future for the country we love. Discover us @ www.govstar.us GovStar is seeking a Full Stack AI Engineer with expert-level Python coding skills and the personal drive to support emerging technology initiatives for national security customers. Ideal candidates will have proven experience building AI applications and architectures. TO APPLY: Please e-mail nicholas.hanson@govstar.us with your resume, a link to your Linkedin profile, and a link to your GitHub profile. PLEASE NOTE: This role does require we validate your Python coding skills, so if you don't have a public GitHub with code samples, we will ask you to take our Python coding challenge. Responsibilities Responsibilities include, but are not limited to: Design, develop, and maintain custom AI applications. Design and implement robust backend services and APIs. Collaborate with data scientists and AI researchers to create new functionality and to integrate AI models into applications. Ensure the performance, quality, and responsiveness of applications. Conduct code reviews and maintain code quality standards. Advise on the latest advancements in AI technologies, tools, and best practices. Preferred Requirements Strong full stack development experience, including proficiency in both frontend development with React, Typescript, and CSS, backend development with Python Strong ability to handle all aspects of a web application, from designing the user interface to managing the server and database Strong experience developing within VSCode for development and workflows and working with GitLab to manage source control and GitLab pipelines Strong experience working with LLMs, including prompt engineering Experience developing with additional programming languages including but not limited to: JavaScript, TypeScript, React, YAML, and JSON Strong working knowledge of Azure development and AI hosting infrastructure Ability to develop and work with APIs, including RESTful services, authentication methods, data formats, and errors Comprehensive understanding of SQL/PostgreSQL and NoSQL databases Experience in integrating SQL/PostgreSQL and NoSQL databases within the same application, when appropriate; and advanced understanding of security best practices for both SQL/PostgreSQL and NoSQL databases Ability to work with data scientist teams to integrate applications with AI/ML, big data, and business intelligence solutions Ability to work independently on a complex task with little direction and management oversight Experience developing solutions using Azure services supporting AI solutions including Azure OpenAI, CosmosDB, and PostgreSQL Experience with Docker and building and deploying applications in Kubernetes containers Experience and knowledge of AI/ML deployments on Azure Familiarity with other front-end tools or Python frameworks Experience developing AI/ML solutions or complex solutions for predictive analytics Experience working in a geographically dispersed, remote team Understanding of Data Science principles and best practices Relevant Technologies Full Stack Development – Python, React, CSS, Typescript Database Management – SQL, PostgreSQL Cloud – Azure Version Control – Git, GitHub Project Management Tools – Jira, Confluence

• Participate in MuleSoft Technical Product and Consulting Services training, methodology and enablement. • Begin participation in field activities with clients by shadowing seasoned architects and practicing enablement gained from training. • Begin to execute MuleSoft implementations for customers and start on your journey to internalise business outcomes and business context relevance to MuleSoft implementation methodologies and approaches. • Complete MuleSoft technical certifications and fully ramp on technology and implementation methodologies; start to develop and contribute subject matter expertise and project deliverables to internal knowledge exchange. • Begin mentorship and guidance of junior Services team members and help to build out our services organisation. • Continue to lead technical teams through multi-phased delivery projects and provide hands-on delivery guidance to influence standards for development, governance, and operational life cycle. • Evangelise frameworks, project deliverables, best practices/policies and implementations to internal collaboration networks and IP sharing. • Identify opportunities to expand MuleSoft footprint and drive further services and customer service, lead multiple engagements simultaneously, and drive partnerships and cross collaboration with MuleSoft partners, SIs and 3rd Parties. • Identify ongoing risks and pain points throughout project experiences in the field and contribute to developing and implementing internal mitigation measures to meet customer needs. • Evangelise, train, coach and mentor Services team members on hard technical skills and soft skills. • Identify opportunities and efficiencies in customer IT operating model, and support implementation of the SDLC pipeline to get greater values out of the MuleSoft platform. • Lead development of technical brown bag sessions and publish/facilitate reusable content to the field. • Work with MuleSoft product leadership providing valuable product insight, guiding product direction and features. • Deliver compelling presentations, architectural blueprint documents, and requirements-gathering workshops to influence the strategic direction of our projects and lead customers through solution design.

• Design, develop, and maintain scalable backend services in Golang, adhering to clean architecture principles and established team standards. • Build and optimize infrastructure for embedding generation, vector search, and/or LLM integration. • Own the full-service lifecycle, including architecture, deployment, monitoring, testing, and scaling. • Write comprehensive unit, integration, and end-to-end tests to ensure high reliability and minimize regressions, following rigorous testing practices. • Collaborate closely with AI/ML engineers, Data Scientists, Architects and other team members, fostering a positive and productive team environment. • Develop pipelines for model serving, versioning, and inference with a focus on latency and robustness. • Monitor production systems, conduct root cause analysis, and proactively resolve issues. • Actively participate in team discussions, code reviews, and knowledge sharing to uphold team standards and continuous improvement.

• Design, build, and maintain database and data integration solutions that support enterprise intelligence and data delivery efforts. • Develop and optimize database structures, implement ETL pipelines, and support data ingestion and transformation across multiple systems. • Ensure data is delivered accurately, efficiently, and securely to downstream users and platforms, while supporting integration efforts across Military Health, readiness, and federal health data sources.