Lockheed MartinRemote
AI Machine Learning Engineer
United States of America
Full Time
6 hours ago
$109,000 - $192,000 USD
No H1B
Key skills
JavaScriptTypeScriptPythonJavaC#Full stack developmentREST APIsGitLabGitHubBitbucketAgile software developmentAI-enabled applicationsLarge language modelsPrompt engineeringSemantic searchWorkflow automationMessage queuesEvent-driven architectureseQubeQuarkusAMQKafkaMuleSoftCamelDevSecOpsCI/CD pipelinesAutomated testingStatic code analysisDependency scanningContainer scanningSecrets managementInfrastructure as codeDockerKubernetesOpenShiftAWSAzureJiraConfluenceArtifactoryJenkinsRelational databasesNoSQL databasesSchema designQuery developmentData modelingAuthenticationAuthorizationRole-based access controlAPI securityAudit loggingTest automationUnit testingIntegration testingAPI testingEnd-to-end testingTest-driven developmentDistributed applications troubleshootingCode reviewsCNoSQLAIMachine LearningLarge Language ModelsETLUnit TestingIntegration TestingGitRepositoryAgileCI/CDLeadershipMentoringCommunication
About this role
Lockheed Martin is a leader in aerospace and defense, seeking an AI Machine Learning Engineer to join their Data & AI Enablement team. The role involves designing and developing software solutions that enhance interoperability between enterprise systems and AI workflows, while collaborating closely with various stakeholders to deliver secure and scalable solutions.
Responsibilities:
- 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
Requirements:
- 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
- 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