• Bachelor’s degree in Computer Science, Software Engineering, or a related technical field
• Minimum 7 years of professional experience developing full‑stack web applications using modern frameworks such as React, Next.js, Node.js, Tailwind CSS
• Familiarity with DevOps best practices, including CI/CD pipelines (GitLab, Azure DevOps)
• Proficiency with cloud platforms (AWS, Azure, or GCP) and containerization technologies (Docker, Kubernetes) for deployment and scaling
• Strong knowledge of relational databases, SQL querying, and API design (REST/GraphQL)
• Demonstrated ability to communicate effectively with non‑technical staff, gathering requirements and translating them into user‑centric software solutions

When it comes to using cutting-edge machine learning to tackle complex problems, Lockheed Martin is driven by a singular mission focus and desire to continuously innovate. Today’s challenges to global security aren’t just changing – they’re accelerating faster than ever before. Through our dedication to our mission, our AI-enabled systems are changing the way militaries operate and protect their forces, the way first responders fight fires, and how researchers explore the far reaches of space and the ocean’s depths.

The Lockheed Martin Artificial Intelligence Center (LAIC) team is seeking a high energy engineer with hands-on experience in developing AI/ML software in support of the AI Consulting team. In this role you will be part of the larger AI Foundations organization consisting of colleagues possessing varying skill sets including AI/Machine Learning specialists, front-end and back-end developers, data engineers, product managers, and other data scientists. The selected candidate will focus on the AI Consulting team, but will be included as part of a broader range of projects across the LAIC portfolio. The AI Consulting team is focused on employing small, innovative, and agile teams to rapidly iterate and mature solutions from prototypes to deployment for utilization across the Lockheed Martin enterprise.
The LAIC AI Consulting Team’s mission includes serving as a center of excellence for AI at Lockheed Martin. The candidate will work to disseminate best practices of the AI Consulting team to other AI and data science teams in the corporation. The candidate will be required to create knowledge materials to publish these best practices, as well as meet with other data science leaders in Lockheed Martin to teach and discuss these practices.

The Full Stack Software Engineer Stf designs, develops, deploys, and supports secure, scalable, and reliable software solutions across the full application lifecycle. The role is responsible for frontend and backend development, API and database design, cloud infrastructure, CI/CD pipelines, security controls, and production application stability.

This position will build and operate AI/ML-enabled web applications, integrating services such as model-serving APIs, LLM providers, vector-search tools, and internal machine-learning platforms. Responsibilities include translating business requirements into user-focused technical solutions; developing responsive interfaces and backend services; and ensuring applications are maintainable, performant, and secure.

The engineer will provide technical leadership in Agile delivery, infrastructure automation, deployment processes, monitoring, incident response, and reliability improvements. The role partners with product, data science, security, infrastructure, operations, and business stakeholders while mentoring engineers and establishing sound engineering standards.

• Experience delivering and operating AI/ML-powered web applications, including integrations with model-serving APIs, LLM providers, embedding or vector-search systems, and internal machine-learning platforms.
• Familiarity with MLOps and LLMOps practices, including model and prompt lifecycle management, evaluation workflows, AI observability, performance monitoring, and safe rollout of AI capabilities.
• Advanced experience owning production CI/CD and release processes across frontend, backend, infrastructure, and containerized services, including automated testing, security scanning, artifact management, deployment controls, and rollback strategies.
• Hands-on experience with Infrastructure as Code and cloud environment management using tools such as Terraform, CloudFormation, Pulumi, Helm, or similar technologies.
• Experience improving the reliability, scalability, and availability of cloud-native applications through Kubernetes operations, autoscaling, networking, secrets management, load balancing, monitoring, alerting, incident response, and capacity planning.
• Strong knowledge of application, cloud, and AI security practices, including secure coding, OWASP guidance, IAM, OAuth/OIDC, secrets management, vulnerability remediation, dependency security, and protections for AI-specific risks such as prompt injection and sensitive-data exposure.
• Experience with asynchronous and event-driven architectures, including message queues, background jobs, streaming workflows, serverless services, or similar patterns.
• Proven technical leadership, including establishing engineering standards, mentoring engineers, and proactively managing production risks related to quality, performance, usability, reliability, and security.
• Experience partnering with product, data science, security, operations, and business stakeholders to deliver practical AI-enabled solutions.