• Develop scalable and maintainable backend systems using Node.js and MongoDB • Collaborate with cross-functional teams to build features for customers and internal tools • Ensure high code quality through unit, integration, and functional testing, code reviews, and thorough documentation • Address challenges in scalability, reliability, and logging during development • Mentor and guide other developers, fostering growth and knowledge-sharing • Stay up-to-date with emerging technologies to keep our team innovative and competitive

Role Description Lockheed Martin is partnering with PG&E, Salesforce, and Wells Fargo to deliver EMBERPOINT™, an initiative designed to transform wildfire prevention, detection, and response across the United States. This position supports a full-time REMOTE telework arrangement, allowing employees to perform their work schedule remotely outside of a Lockheed Martin designated office or job site. As a Software Engineer supporting the Unified HMI platform, you will help build modern, mission-focused systems that fuse AI/ML insights, real-time operational data, and cloud-native infrastructure into a cohesive operational environment. You will work across backend services, middleware, DevSecOps, cloud integration, and real-time data processing activities to support systems that enable the full Detection → Prediction → Response → Recovery workflow. Key Responsibilities - Build backend and middleware services to ingest and process real-time sensor, telemetry, and AI/ML data streams. - Develop and maintain cloud-native applications and integrations leveraging AWS services and modern software architectures. - Support DevSecOps activities including CI/CD pipeline development, automated testing, and deployment processes. - Develop unit, integration, and automation tests to validate functionality and system performance. - Participate in Agile and SAFe development activities including PI Planning, Scrum of Scrums, and System Demonstrations. - Collaborate with architects, AI/ML engineers, software developers, and stakeholders to ensure solutions support operational workflows and mission objectives. - Produce technical documentation including design specifications, API documentation, and implementation guidance. Qualifications - B.S. in Computer Science, Software Engineering, Electrical Engineering, or related field (M.S. preferred). - 4+ years professional software development. - Proficiency in Python, Fast API, AWS, Oracle OCI, Kubernetes, Docker, Web Sockets, REST APIs, GitLab, and Linux. - Experience building and maintaining CI/CD pipelines (GitLab CI, Jenkins, Azure DevOps) and using static/dynamic security tooling. - Experience with Unit test frameworks and UI-automation Agile/SAFe execution, JIRA/Confluence, and ability to produce clear technical documentation. Requirements - Hands-on data integration experience with Kafka, MQTT, AWS Kinesis/AppSync, REST/GraphQL, and experience handling high-velocity streaming data. - Experience with micro services development. - Experience with AWS services and Infrastructure-as-Code. - Familiarity with MBSE tools (Cameo → DOORS NEXT) and the ability to surface model-derived data in the UI. - Background in AI/ML explainability visualizations integrated into the operator dashboard. - Experience with streaming real-time video. - Certifications: Microsoft Certified: Azure Developer Associate, AWS Certified Solutions Architect – Professional, IAAP CPACC (accessibility), or CISSP (security). Benefits - Medical, Dental, Vision, Life Insurance, Short-Term Disability, Long-Term Disability, 401(k) match, Flexible Spending Accounts, EAP, Education Assistance, Parental Leave, Paid time off, and Holidays.

• Deploy, orchestrate, and maintain AI applications in high-availability production environments • Develop and maintain complex system integrations using REST/GraphQL APIs, API Gateways, and Load Balancers • Build data pipelines and processing workflows for AI applications using Python in AWS environments • Design, optimize, and support architectures based on Agentic AI and Agent-to-Agent (A2A) communication • Implement and support integrations using MCP (Model Context Protocol) • Evolve and maintain OCR pipelines and unstructured data extraction workflows using LLMs • Create, manage, and enhance advanced monitoring and observability dashboards to ensure model health, inference performance, application availability, and operational cost control using Grafana, Rancher, and related tools • Monitor and optimize AI applications in production to ensure scalability, stability, and operational efficiency • Identify and resolve performance issues, bottlenecks, and failures in AI pipelines • Collaborate with cross-functional engineering, data, architecture, and product teams

• Capture technical requirements and contribute to high-level and low-level design for software solutions using AWS and Azure technologies. • Write production-grade Python, and SQL code that meets high standards for maintainability, security, and observability. • Build and support complex, microservice-based, event-driven systems. • Collaborate across engineering, design, and product to deliver high-quality outcomes. • Participate in on-call rotation and help maintain system health, performance, and reliability.