AI Machine Learning Engineer

Basic Qualifications Experience developing software using one or more modern programming languages, such as JavaScript, TypeScript, Python, Java, C#, or similar. Experience developing full stack applications, including user interface, back-end service, API, and database components. Experience designing, developing, or consuming REST APIs or similar integration interfaces. Experience with Git-based software configuration management tools, such as GitLab, GitHub, Bitbucket, or similar. Experience working in an Agile software development environment.Job DescriptionData & AI Enablement is seeking a Senior Full Stack Engineer to join the Enterprise Interoperability Framework team. This team designs, develops, and supports software solutions that enable interoperability between disparate enterprise systems, data platforms, development tools, and AI-enabled workflows.The candidate will work as part of an agile engineering team and will be expected to contribute across the full software development lifecycle, including requirements analysis, system design, front-end and back-end development, API integration, automated testing, deployment support, troubleshooting, and sustainment. The role requires close collaboration with product owners, software engineers, data engineers, AI/ML practitioners, cybersecurity teams, DevSecOps teams, and business stakeholders to deliver secure, scalable, and maintainable solutions.Responsibilities May Include Designing and developing full stack software solutions using modern front-end, back-end, database, and API technologies. Building integrations between enterprise systems through REST APIs, event-driven patterns, middleware (e.g. eQube, Quarkus, AMQ), ETL/data pipelines, and automation frameworks. Developing AI-enabled capabilities that incorporate large language models, AI services, prompt engineering, model APIs, semantic search, document analysis, or intelligent workflow automation. Creating and maintaining APIs and services that support interoperability, data exchange, system synchronization, and workflow orchestration. Implementing secure software engineering practices aligned with enterprise cybersecurity, DevSecOps, and data governance requirements. Collaborating with cross-functional teams to translate business needs into technical solutions and deliver capabilities in an agile environment. Troubleshooting complex integration issues involving data mappings, authentication, API behavior, system dependencies, performance, and reliability. Supporting CI/CD pipelines and deployment activities for cloud, containerized, or enterprise-hosted applications. Providing technical leadership within the team, including solution design input, code reviews, mentoring, and guidance on engineering best practices.What’s In It For YouFrom onsite to remote, we offer flexible work schedules to comprehensive benefits investing in your future and security, Learn more about Lockheed Martin’s comprehensive benefits package here.Do you want to be part of a company culture that empowers employees to think big, lead with a growth mindset, and make the impossible a reality? We provide the resources and give you the flexibility to enable inspiration and focus -if you have the passion and courage to dream big, work hard, and have fun doing what you love then we want to build a better tomorrow with you.#EBDTDesired Skills Experience developing AI-enabled applications, including integration with large language models, AI APIs, retrieval-augmented generation, semantic search, embeddings, prompt engineering, or intelligent workflow automation. Experience building enterprise system integrations using REST APIs, message queues, event-driven architectures, middleware, ETL/data pipelines, or workflow automation. Experience with integration or middleware technologies, such as eQube, Quarkus, AMQ, Kafka, MuleSoft, Camel, or similar. Experience with DevSecOps practices, including CI/CD pipelines, automated testing, static code analysis, dependency scanning, container scanning, secrets management, or infrastructure as code. Experience with cloud or container platforms, such as Docker, Kubernetes, OpenShift, AWS, Azure, or similar. Experience with enterprise software development tools, such as GitLab, Jira, Confluence, Artifactory, Jenkins, or similar. Experience with Jira or GitLab APIs, webhooks, workflow automation, issue synchronization, merge request workflows, or repository automation. Experience with relational or NoSQL databases, including schema design, query development, data modeling, or application integration. Experience with secure software development practices, including authentication, authorization, role-based access control, API security, audit logging, and secure handling of sensitive data. Experience with test automation, including unit testing, integration testing, API testing, end-to-end testing, or test-driven development. Experience troubleshooting distributed applications or integrations, including API behavior, data mapping, authentication, system dependencies, observability, performance, and reliability. Experience mentoring engineers, leading technical design discussions, performing code reviews, or establishing engineering best practices. Strong written and verbal communication skills, including the ability to communicate technical concepts to technical and non-technical stakeholders.Other Important InformationBy applying to this job, you are expressing interest in this position and could be considered for other career opportunities where similar skills and requirements have been identified as a match. Should this match be identified you may be contacted for this and future openings.Ability to work remotelyFull-time Remote Telework: The employee selected for this position will work remotely full time at a location other than a Lockheed Martin designated office/job site. Employees may travel to a Lockheed Martin office for periodic meetings.