Director, AI Enterprise Transformation

Constellis • Herndon, VA

9h • Onsite

About The Position

The Director of AI Enterprise Transformation leads Constellis’ enterprise technology evolution by setting the roadmap and delivering high-impact AI, analytics, and automation solutions that improve operational performance, contract compliance, and mission readiness in complex government environments. This hands-on, player/coach role leads AI strategy while directly designing, building, deploying, and operating production capabilities (e.g., Python/SQL, data pipelines, dashboards, integrations/APIs, and MLOps).

Requirements

• 10+ years delivering digital transformation with hands-on engineering in government, defense, or security operations.
• Bachelor’s degree in Computer Science, Software Engineering, Computer Engineering, Data Science, Information Systems, or a related technical discipline (or equivalent practical experience).
• Experience deploying AI/ML, generative AI, RPA, and analytics solutions in secure, compliance-driven environments.
• Hands-on ERP/CRM/HRIS integration experience (connectors, ETL/ELT, APIs).
• Strong cybersecurity and governance foundation (CMMC, NIST, ISO 27001, ITAR, FISMA) with secure-by-design implementation experience.
• Player/coach leadership with engineering standards, code/design reviews, and Agile/DevOps delivery.
• AI security, privacy, and compliance knowledge (governance, access, auditability).
• Experience as a Forward Deployed Engineer, Solutions Engineer, or Technical Architect.
• Familiarity with enterprise productivity platforms (Microsoft 365/Copilot, Google Workspace).
• Enterprise architecture (reference architectures, integration patterns, delivery).
• ERP/CRM/HRIS platforms (e.g., Costpoint, Workday, Salesforce, ServiceNow), including configuration and API/data integrations.
• Systems integration (APIs, iPaaS/middleware, data pipelines) with testing and production support.
• Workflow/BPM tools (process design, automation, release/documentation).
• Ability to build curated datasets with data modeling and SQL (transforms, reporting).
• Ability to deliver BI in Power BI/Tableau/Qlik (dashboards/models) with governed datasets and access controls.
• Ability to develop and deploy AI/ML in Python (data prep, feature engineering, training, evaluation, monitoring).
• Ability to implement GenAI solutions (prompting, RAG, vector search, evaluation, guardrails).
• Data/model governance (quality, lineage, validations, documentation).
• Cloud (Azure/AWS/GovCloud) experience: deploy apps and AI workloads; integrate PaaS/SaaS; manage environments with DevOps.
• Zero-trust and IAM patterns (SSO, MFA, RBAC/ABAC).
• Experience with FedRAMP/CMMC/NIST 800-53/171 environments; secure SDLC for data and AI systems (CI/CD, config, audit evidence).
• Networking/infrastructure basics and observability (logging, metrics, alerting).
• Automation (UiPath/Power Automate/Automation Anywhere): build and integrate workflows, including AI-enabled steps.
• Low-code/no-code governance and pro-code transition criteria.
• Content/document management (SharePoint, forms, e-signature) with automation and integrations.
• Delivery tooling (Jira, Azure DevOps, MS Project, Smartsheet): backlogs, releases, risks.
• Agile/hybrid delivery (Scrum, Kanban) with modern engineering (Git, reviews, CI/CD).
• Technical/operational risk management (change control, incidents, RCA, continuous improvement).
• Understanding of cost/billing rules and how they shape integrations, data models, and controls.
• Familiarity with contract systems and CLIN/TO/IDIQ structures for compliance and forecasting reporting.
• Awareness of ITAR/EAR constraints (data location, access, source code, administration).

Nice To Haves

• Master’s degree preferred (e.g., Computer Science, Data Science, Engineering Management, or MBA with a technology focus).

Responsibilities

• Define the transformation roadmap and deliver priority solutions from prototype to production (Python/SQL, pipelines, dashboards, APIs).
• Own the AI roadmap and deliver prioritized use cases from design through production with IT and business stakeholders.
• Build and deploy AI-enabled automation and analytics (predictive, anomaly, optimization) that measurably improve decision-making and operations.
• Establish engineering standards and reusable components; mentor through pairing and code/design reviews.
• Implement MLOps and operational support (CI/CD, evaluation, monitoring, telemetry, controlled releases) to improve reliability and ROI.
• Modernize and integrate ERP/CRM/HRIS and mission-support systems, including hands-on integrations and automation.
• Implement and enforce data governance and quality controls by building and operating governed datasets and data pipelines (ETL/ELT), developing data validations and reconciliations, and maintaining data definitions/documentation that meet federal data protection requirements while enabling analytics and business intelligence capabilities.
• Ensure all delivered solutions meet cybersecurity, CMMC, and FedRAMP requirements by implementing technical controls in code and configuration (access, secrets management, logging, encryption, secure configurations, and data handling), following secure SDLC practices, and driving remediation in coordination with IT Security.
• Drive adoption of delivered capabilities by providing practical documentation, training, and support, and by partnering with stakeholders to align workflows and operating procedures with new digital tools.
• Partner with Operations, HR, Finance, and Program Management to translate mission needs into technical requirements and deliver solutions that fit high-consequence operational environments.
• Coordinate with external vendors and partners as required, while retaining internal ownership for architecture decisions, integration, testing, and delivery of outcomes.
• Define success measures, report outcomes, and support ongoing operations of delivered solutions.
• Own customer-facing AI deployments from discovery through production.
• Clarify workflows, data, constraints, and success criteria.
• Feed field insights to Product, Platform, and Research.
• Harden deployments with monitoring, runbooks, and best practices.
• Provide clear documentation and knowledge transfer.
• Support architecture reviews and proof-of-concepts.

Benefits

• Constellis offers a comprehensive, total rewards package that includes competitive compensation and a flexible benefits package that reflects its commitment to creating a diverse and supportive workplace.

What This Job Offers

• Job Type: Full-time
• Career Level: Director
• Number of Employees: 5,001-10,000 employees