Standard Job Description

Responsible for developing, integrating, and deploying autonomy and artificial intelligence algorithms for mission systems, supporting the technology development life cycle from requirements generation through development, integration, and testing, as well as research in some organizations. Develops, integrates, and implements algorithms to enable perception, motion/mission planning, controls, etc. functionality in LM products and platforms; Translates requirements and applies requirements to development code, integrating autonomy, AI or machine learning algorithms to LM products and platforms; Determines software methods to best acquire and execute knowledge; Implements algorithms into software to train systems to recognize patterns and perform specific functions; Responsible for various phases of developing and maintaining autonomy software from requirements generation, software design and development to integration, testing, troubleshooting and debugging, and implementation; Review test outcomes, conducts troubleshooting, and works to debug issues; Develops human-machine interface scenarios, breaking missions into tasks; Documents interface requirements and implements human-machine interfaces.

The Lockheed Martin Artificial Intelligence Center (LAIC) seeks a curious and action-biased AI Adoption Analytics & Data Specialist with a strong background in data engineering, generative AI, and developer enablement. This role blends data pipeline engineering with user and executive storytelling to support enterprise-wide AI transformation. You’ll design and maintain the data infrastructure that powers AI adoption & tokenomics measurement to ensure these solutions deliver measurable impact for Lockheed Martin teams.

Data Pipeline Design & Development

• Architect and implement end-to-end data pipelines that ingest, transform, and deliver data from diverse enterprise sources to support AI adoption programs and analytics.
• Design ETL/ELT workflows using Python, SQL, Flyte, and/or similar orchestration tools to process structured and unstructured data at scale.
• Build and maintain data models optimized for AI/ML datasets, adoption metrics, and executive visualizations.
• Develop automated data quality checks, validation rules, and monitoring to ensure pipeline reliability and data integrity.

AI Adoption Analytics & Measurement

• Create data infrastructure supporting AI adoption KPIs.
• Build pipelines that aggregate and normalize data from Generative AI and other internal AI platforms to provide unified adoption reporting.
• Synthesize adoption metrics, developer feedback, and market trends into executive-ready reports and decision packages.
• Develop real-time and batch data feeds for leadership dashboards that track AI maturity across business areas and programs.

Data Integration, Governance & Security

• Integrate data from multiple internal platforms, HR systems, learning management systems, and AI tools into cohesive, AI-ready datasets.
• Document data lineage, maintain data dictionaries, and enforce governance standards across all pipeline outputs.
• Collaborate with cybersecurity and IT teams to ensure secure data transfer and storage within on-premises and classified environments.

Community & Ecosystem Development

• Serve as a bridge between developers, data teams, product teams, and leadership to ensure alignment on priorities and roadmap.
• Contribute to the AI Factory ecosystem by developing reusable data components, integration patterns, and shared services.
• Partner with engineering leaders to identify tool and solution gaps, and influence product direction based on developer feedback and adoption data.
• Provide technical guidance to junior team members on data engineering best practices.

Basic Qualifications

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related STEM field.
• 5+ years of professional experience in data engineering, data pipeline development, AI strategy, developer relations, or technical program management.
• Proficiency in Python and SQL for data manipulation, transformation, and pipeline automation.
• Hands-on experience with data orchestration tools (Flyte, AirByte, Apache Airflow, Prefect, Luigi, or equivalent).
• Experience with relational databases (PostgreSQL, MySQL, or similar).
• Strong technical understanding of generative AI, developer tools, and modern software development workflows.
• Excellent communication and storytelling skills, with the ability to engage both technical and executive audiences.

Desired Skills

• Experience with data pipelines in defense, aerospace, or highly regulated industries.
• Familiarity with AI/ML data preparation workflows, feature engineering, and training data management.
• Experience with streaming data platforms (Kafka, Spark Streaming, or equivalent).
• Knowledge of data visualization tools (Streamlit, React, Power BI, or Grafana) for dashboard integration.
• Hands-on experience with AI-assisted development tools (e.g., GitHub Copilot, ChatGPT, internal LLMs).
• Proven ability to build and sustain technical communities.
• Exposure to containerization (Docker, Kubernetes) and CI/CD for data pipeline deployment.
• Experience with API development (REST, GraphQL) for data service layers.
• Familiarity with Lockheed Martin internal platforms (Navigator, Genesis, AI Factory).