Accenture
Data & AI Strategy Senior Manager
$149K–$306K
Washington, DC +1 · Manager · Full-time · Posted Jun 8, 2026
- Location
- Washington, DC
Arlington, Virginia, United States - Experience
- 10+ years of technical experience; no alternative stated.
- Education
- Bachelor's Degree
- Visa sponsorship
- US citizenship required. Applicants must have US work authorization that does not now or in the future require visa sponsorship.
About the job
Leads client Data & AI strategy engagements, teams, and deliverables, translating data and AI opportunities into strategic recommendations and implementation plans for federal and other clients.
What you'll do
- Lead and mentor cross-functional teams, oversee client deliverables, and advise clients on Data & AI strategy and implementation.
- Engage senior stakeholders, facilitate workshops, and communicate recommendations through presentations and board papers.
- Analyze data, develop thought leadership and intellectual property, and collaborate with AI labs to drive innovative solutions.
What they ask for
- 10+ years of technical experience focused on data engineering, AI/ML systems, or related fields.
- Hands-on expertise in data architecture, pipeline development, and AI/ML platform design; experience with modern data technologies.
- Technical leadership managing engineering teams on complex programs; working knowledge of ML engineering, model deployment, and MLOps frameworks.
- Experience in Defense, Intelligence, or Federal environments; demonstrated cross-functional leadership; Bachelor's Degree.
Nice to have
- Hands-on experience with listed technologies such as Databricks, Palantir, Snowflake, Kubernetes, Python, and Spark.
- Defense- or Intelligence-specific platforms, Agile delivery in classified or secure environments, or executive-level communication skills.
Pay
$148,800 — $306,500 USD (base salary)
Tools
Databricks, Palantir, Snowflake, Qlik, Kubernetes, Terraform, Python, Spark
AI focus
Leads Data, AI, and GenAI strategy; advises on AI/ML platforms, ML engineering, deployment, and MLOps; identifies use cases and supports implementation.
Model-written summary · the original posting is authoritative