The Work:Lead enterprise AI strategy, delivery, and governance using Gemini for Enterprise, Vertex AI, and modern ML/GenAI technologies. Drive high-impact AI initiatives, build scalable platforms, and guide cross-functional teams.
Key Responsibilities:- Define AI vision, strategy, and roadmap aligned to business goals.
- Identify high-value AI/ML use cases across operations, customer experience, risk, and productivity.
- Architect and deliver end-to-end AI/ML solutions (LLMs, RAG, pipelines, MLOps, CI/CD).
- Lead workshops, stakeholder alignment, and executive communication.
- Oversee model governance, responsible AI, security, compliance, and performance tracking.
- Mentor data scientists, ML engineers, analysts, and platform engineers.
Here is what you need:- US Citizen (Public Trust Eligible)
- 3+ years of experience in leading technical teams to achieve objectives and outcomes. Experience includes
- Developing and implementing technical standards, systems and processes for cloud and on-prem environments.
- Recommending technology strategies and decisions with a high-level of expertise and knowledge.
- Providing technical direction and support to ensure compliance with standards and guidelines
- 3+ years leading AI/ML teams or initiatives in complex enterprise environments.
- Demonstrated experience delivering end to end AI/ML solutions using Vertex AI, Gemini APIs, or other cloud AI platforms.
- Solid understanding of generative AI, LLMs, retrieval-augmented generation (RAG), embeddings, and vector databases.
- Google Storage: Access control, versioning, encryption, lifecycle management, storing logs, handling backups, managing static files, working with ML workflows, Storage Transfer Service, Cloud Storage, Cloud Storage for Firebase, Filestore, Google Workspace Essentials, Local SSD, Persistent Disk
- DevOps/Configuration Management/Help Desk: Ansible, Cloudockit, GitHub, Jira ServiceDesk, ServiceNow
- Experience with Google Cloud GenAI tools, including Vertex AI Search, Vector Search, Agents, and Workbench
- Familiarity with responsible AI frameworks, model governance, and risk management.
- Experience with Kubernetes, microservices, and distributed systems.
- Industry certifications (e.g., Google Cloud Professional ML Engineer, Data Engineer, or Architect).
- Strong leadership, communication, and stakeholder management.
Preferred Experience:- Master's/PhD in AI/ML or related field
- Regulated environment experience (FedRAMP, HIPAA, PCI, NIST)
- AI modernization or cloud migration leadership
As required by local law, Accenture Federal Services provides reasonable ranges of compensation for hired roles based on labor costs in the states of
California, Colorado, Connecticut, Hawaii, Illinois, Maine, Maryland, Massachusetts, Minnesota, New Jersey, New York, Ohio, Vermont, Virginia, Washington, and the District of Columbia. The base pay range for this position in these locations is shown below. Compensation for roles at Accenture Federal Services varies depending on a wide array of factors, including but not limited to office location, role, skill set, and level of experience. Accenture Federal Services offers a wide variety of benefits. You can find more information on benefits here. We accept applications on an on-going basis and there is no fixed deadline to apply.
The pay range for the states of California, Colorado, Connecticut, Hawaii, Illinois, Maine, Maryland, Massachusetts, Minnesota, New Jersey, New York, Ohio, Vermont, Virginia, Washington, and the District of Columbia is:
$103,200-$196,400 USD
