Vice President of Applications

Vice President, Software Engineering & Enterprise Analytics

Location: On-site in Arlington VA

A large-scale, multi-site energy organization is seeking a Vice President of Software Engineering & Enterprise Analytics to define and execute the company’s technical vision across software development, enterprise data platforms, advanced analytics, and artificial intelligence. Reporting to the CIO, this executive will drive innovation, build scalable digital ecosystems, and elevate engineering and analytics maturity across the enterprise.

This leader will guide teams responsible for software engineering, data engineering, data science, enterprise analytics, and AI/ML solution development. The role requires a blend of strategic foresight, organizational leadership, deep technical fluency, and the ability to translate business needs into high-impact digital capabilities.

Key Responsibilities

Strategic Technology Leadership

• Build and deliver a unified roadmap for enterprise software, data platforms, analytics, and AI/ML solutions.
• Establish engineering and analytics standards, governance models, and technology-wide architecture principles.
• Lead modernization initiatives including cloud transformation, platform consolidation, legacy refactoring, and enterprise AI enablement.
• Present KPIs, value realization, and strategic impact to executive stakeholders.

Software Engineering Excellence

• Oversee design, development, deployment, and lifecycle management of custom applications and enterprise digital platforms.
• Champion engineering best practices including Agile delivery, CI/CD, DevSecOps, test automation, and code quality.
• Approve enterprise architecture decisions and major systems designs.
• Lead platform evaluations, vendor management, and integration strategy.

Enterprise Analytics, Data, and AI

• Direct enterprise data strategy including data engineering, governance, lineage, quality, and metadata management.
• Oversee enterprise analytics services—BI, dashboards, KPI frameworks, predictive analytics, and decision-support tools.
• Lead development and deployment of AI/ML solutions using enterprise-grade platforms such as: Azure Machine Learning, AWS SageMaker, Google Vertex AI; Databricks, Snowflake Snowpark, H2O.ai, DataRobot, NVIDIA AI frameworks; Kubeflow, MLflow, Airflow, or other model lifecycle orchestration systems
• Drive adoption of AI for operational efficiency, anomaly detection, reliability optimization, forecasting, automation, and intelligent decision systems.
• Promote responsible AI practices, model governance, and scalability across business units.

Cross-Functional Partnership

• Partner with leaders across operations, commercial, finance, supply chain, and plant/field functions to identify high-value digital opportunities.
• Convert business challenges into integrated technology roadmaps and strategic programs.
• Act as a trusted advisor to senior leadership on software, data, analytics, and AI strategy.

Organizational Leadership

• Build, mentor, and retain high-performing software engineering, analytics, data science, and data engineering teams.
• Oversee budgets, staffing, capacity planning, and vendor/partner ecosystem management.
• Shape an innovative, inclusive, performance-oriented culture.
• Establish professional development pathways and succession planning.

Additional Responsibilities

• Ensure compliance with corporate policies, cybersecurity standards, and regulatory requirements.
• Maintain awareness of emerging technologies in software engineering, cloud ecosystems, industrial automation, and enterprise AI.
• Participate in steering committees and cross-functional leadership forums.
• Support special projects and technology initiatives as needed.

Qualifications

• Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field; master’s preferred.
• 10 years of progressive leadership across software engineering, enterprise data, analytics, AI/ML, or platform engineering.
• At least 2 years in an executive or senior leadership role overseeing multi-disciplinary technical teams.
• Proven success deploying enterprise-scale platforms integrating application development, data engineering, and advanced analytics/AI.
• Deep expertise in:
• Application architecture and distributed systems
• Enterprise AI/ML platforms (SageMaker, Vertex AI, Azure ML, Databricks, H2O.ai, etc.)
• Data warehousing/lakehouse technologies
• BI and visualization platforms
• Strong executive communication skills and the ability to influence senior leadership.
• Business acumen and the ability to tie technology strategy directly to measurable outcomes.
• Commitment to building diverse, equitable, and inclusive teams.