CentralSquare Technologies is dedicated to empowering public servants and uplifting communities through advanced technology. The Director of AI Engineering Operations will lead the transformation of product and engineering teams to embed AI capabilities throughout the software development lifecycle, ensuring high-quality outcomes and effective governance.
Responsibilities:
- Own the AI program roadmap in partnership with the CTO, aligning initiatives to business priorities and technology strategy
- Establish and lead the AI Operations Center of Excellence (CoE), setting standards for model development, deployment, monitoring, and governance
- Drive portfolio-level visibility into all AI/ML workstreams, ensuring executive stakeholders have clear line of sight into progress, risks, and ROI
- Define and track KPIs for AI operational maturity, model performance, and business impact
- Develop and enforce the company's AI governance framework, including responsible AI principles, model risk management, and bias/fairness evaluation standards
- Collaborate with legal, security, and privacy teams to ensure AI deployments comply with applicable regulations (e.g., EU AI Act, CCPA, HIPAA where relevant)
- Maintain an AI model inventory and risk register; coordinate audits and third-party assessments
- Champion ethical AI practices across the organization, facilitating training and awareness programs
- Manage relationships with AI platform vendors, cloud providers, and third-party model suppliers (e.g., OpenAI, Anthropic, Google, AWS, Azure AI)
- Lead evaluation, procurement, and contracting for AI tooling and foundation model APIs; negotiate SLAs and data processing agreements
- Monitor the external AI landscape to surface emerging capabilities and competitive risks relevant to the company's strategy
- Conduct a comprehensive assessment of existing SDLC processes across the portfolio and lead the strategic transformation of development teams toward an AI-native engineering model, establishing modern practices that embed AI capabilities throughout the full software delivery lifecycle
- Foster a culture of experimentation, accountability, and continuous learning within the team
- Develop talent pipelines and upskilling programs in partnership with HR and Learning & Development
Requirements:
- 12+ years of progressive experience in technology, with at least 2+ years in transforming AI/ML operations, platform engineering, or related technical leadership roles
- Demonstrated track record of taking AI/ML systems from prototype to production at scale
- Deep familiarity with MLOps tooling (e.g., MLflow, Kubeflow, SageMaker, Vertex AI, Azure ML) and cloud-native AI infrastructure
- Strong working knowledge of LLMs, generative AI, and prompt engineering patterns; experience operating LLM-based applications in production
- Experience designing and implementing AI governance frameworks, model risk management, or responsible AI programs
- Proven ability to lead cross-functional programs and influence stakeholders without direct authority
- Excellent communication skills; ability to synthesize complex technical topics for executive audiences