Job description

The Director, Applied AI leads Covista's Applied AI team within Enterprise Data & Insights (EDI) — the single team that designs, builds, and operates Covista's agentic AI capability across all four school brands. This role owns three delivery PODs: No/Low/Medium-Code Agents, High-Code/Full-Code Agents, and Robotic Process Automation. As the accountable owner of Applied AI's portfolio, Responsible-AI posture, and partner ecosystem, you will build out a fully staffed FTE core (Principal AI/Agent Architect, Responsible AI/Risk & Safety Lead, AI Evaluation Engineer), govern platform architecture and vendor delivery, and ensure every agent shipped is safe, evaluated, and measurably valuable to the business. Strategic Leadership & Portfolio Ownership • Own and evolve the Applied AI strategy across all three delivery PODs, ensuring alignment with EDI's broader data & AI roadmap and Covista's enterprise architecture principles. • Serve as the single accountable leader for the full spectrum of automation and agentic AI work — from deterministic RPA bots to full agentic systems. • Represent Applied AI in EDI leadership forums, partnering closely with the Sr Directors of Data Science, Data Engineering, and Data Reporting & Analytics. Platform Architecture & Technology Oversight • Partner with the Principal AI/Agent Architect to set and enforce the reference architecture: Vertex AI Agent Engine patterns, the Agent Development Kit (ADK), the MCP tool catalog, and model-routing rules across Anthropic, Google, OpenAI, and Microsoft models. • Ensure every new agent design is reviewed against reference architecture before entering the backlog, across all three PODs. • Drive standardization and modernization of the platform, emphasizing scalability, reusability, and reduced technical debt. Responsible AI & Governance • Own overall accountability for Responsible-AI posture, with the Responsible AI/Risk & Safety Lead operating a dotted line into the Covista AI Governance Board. • Ensure risk tiering; FERPA/HIPAA/GLBA review gates, red-team coordination, model cards, and bias evaluation are applied consistently to every agent and automation before release. • Require eval-case authorship as a contractual deliverable on every Applied AI build statement of work — no eval, no production. Delivery, Partner & Vendor Management • Manage delivery partner relationships (AheadRace, SoftServe, Stefanini) including SOW governance, two-vendor resilience planning for critical roles, and quarterly partner scorecards. • Route every partner engagement above $250K/year to the Covista Enterprise Architecture Review Board prior to contract signature. • Own intake and prioritization across the Applied AI backlog, ensuring efficient allocation of FTE and contract capacity. Evaluation & Quality Oversight • Hold the AI Evaluation Engineer accountable for a durable eval harness — offline golden datasets, regression suites, LLM-as-judge scoring, human-review queues, and online quality monitoring. • Treat evaluation data as protected Covista IP that stays inside the organization, never delegated wholesale to a delivery partner. People Leadership & Team Building • Lead and mentor the current Applied AI core team (Technical Lead, Product Owner, Scrum Master, AI Engineer) plus the RPA POD (RPA Architect & Product Owner and RPA developers). • Execute the FY27 conservative-MVP hiring plan: Principal AI/Agent Architect, Responsible AI/Risk & Safety Lead, and AI Evaluation Engineer, and prepare the FY28 roadmap hires pending demonstrated value. • Cultivate a high-performing, inclusive culture with a focus on continuous improvement, technical excellence, and safe experimentation. Cross-Functional Collaboration • Maintain a clear routing boundary with CVSA AI Solutions (full-code AI products) and the chatbot/aggregation team, ensuring work reaches the right team the first time. • Partner with business sponsors across Covista's school brands to translate demand into a prioritized, governed agent backlog. • Performs other duties as assigned. • Complies with all policies and standards. • Bachelor's Degree Computer Science, Data Science, Artificial Intelligence, Engineering, or related field. Required • Master's Degree MS in Computer Science/AI, or MBA. Preferred • Cloud/AI certification (e.g., Google Cloud Professional ML Engineer, AWS/Azure AI Engineer Associate). Preferred. • Ten (10) plus years experience in enterprise technology leadership roles. • Five (5)plus years experience leading AI/ML, data, or platform engineering teams, including management of outsourced/SOW-based delivery partners. • Experience in higher education, healthcare, or other complex, regulated, matrixed environments. • Experience with agentic AI platforms (Vertex AI Agent Engine, ADK, MCP) and Responsible-AI/model-risk governance. • Deep expertise in agentic AI architectures and enterprise AI platforms — Vertex AI Agent Engine, the Agent Development Kit (ADK), the Model Context Protocol (MCP), and multi-model orchestration across Anthropic, Google, OpenAI, and Microsoft. • Proven track record building, scaling, and retaining high-performing AI/ML or platform engineering teams. • Experience implementing Responsible-AI governance: risk tiering, model cards, bias evaluation, red-teaming, and regulatory review gates (e.g., FERPA, HIPAA, GLBA). • Strong vendor and partner management skills, including SOW governance, architecture review boards, and delivery of scorecards. • Strategic financial acumen — budget ownership, compensation planning, and build-vs-buy-vs-partner decision-making. • Strong stakeholder management skills with the ability to work across business and technology domains. • Demonstrated leadership abilities and excellent written and oral communication skills. • Highly organized and able to manage multiple concurrent initiatives and cross-functional teams simultaneously. In support of the pay transparency laws enacted across the country, the expected salary range for this position is between $100,171.61 and $181,034.70. Actual pay will be adjusted based on job-related factors permitted by law, such as experience and training; geographic location; licensure and certifications; market factors; departmental budgets; and responsibility. Our Talent Acquisition Team will be happy to answer any questions you may have, and we look forward to learning more about your salary requirements. The position qualifies for the below benefits. Covista offers a robust suite of benefits including: • Health, dental, vision, life and disability insurance • 401k Retirement Program + 6% employer match • Participation in Covista’s Flexible Time Off (FTO) Policy • 12 Paid Holidays For more information related to our benefits please visit: careers.covista.com You are also eligible to participate in an annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance. Equal Opportunity – Minority / Female / Disability / V / Gender Identity / Sexual Orientation

Requirements

Must-haves

Strategic Leadership & Portfolio Ownership
Own and evolve the Applied AI strategy across all three delivery PODs, ensuring alignment with EDI's broader data & AI roadmap and Covista's enterprise architecture principles.
Serve as the single accountable leader for the full spectrum of automation and agentic AI work — from deterministic RPA bots to full agentic systems.
Represent Applied AI in EDI leadership forums, partnering closely with the Sr Directors of Data Science, Data Engineering, and Data Reporting & Analytics.
Platform Architecture & Technology Oversight
Ensure every new agent design is reviewed against reference architecture before entering the backlog, across all three PODs.
Drive standardization and modernization of the platform, emphasizing scalability, reusability, and reduced technical debt.
Responsible AI & Governance
Own overall accountability for Responsible-AI posture, with the Responsible AI/Risk & Safety Lead operating a dotted line into the Covista AI Governance Board.
Ensure risk tiering; FERPA/HIPAA/GLBA review gates, red-team coordination, model cards, and bias evaluation are applied consistently to every agent and automation before release.
Require eval-case authorship as a contractual deliverable on every Applied AI build statement of work — no eval, no production.
Delivery, Partner & Vendor Management
Manage delivery partner relationships (AheadRace, SoftServe, Stefanini) including SOW governance, two-vendor resilience planning for critical roles, and quarterly partner scorecards.
Route every partner engagement above $250K/year to the Covista Enterprise Architecture Review Board prior to contract signature.
Own intake and prioritization across the Applied AI backlog, ensuring efficient allocation of FTE and contract capacity.
Evaluation & Quality Oversight
Hold the AI Evaluation Engineer accountable for a durable eval harness — offline golden datasets, regression suites, LLM-as-judge scoring, human-review queues, and online quality monitoring.
Treat evaluation data as protected Covista IP that stays inside the organization, never delegated wholesale to a delivery partner.
People Leadership & Team Building
Lead and mentor the current Applied AI core team (Technical Lead, Product Owner, Scrum Master, AI Engineer) plus the RPA POD (RPA Architect & Product Owner and RPA developers).
Execute the FY27 conservative-MVP hiring plan: Principal AI/Agent Architect, Responsible AI/Risk & Safety Lead, and AI Evaluation Engineer, and prepare the FY28 roadmap hires pending demonstrated value.
Cultivate a high-performing, inclusive culture with a focus on continuous improvement, technical excellence, and safe experimentation.

Nice-to-haves

Master's Degree MS in Computer Science/AI, or MBA. Preferred
Cloud/AI certification (e.g., Google Cloud Professional ML Engineer, AWS/Azure AI Engineer Associate). Preferred.

Application prep

Use the role’s language and application details while tailoring your materials.

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Benefits

Benefits detected in the listing.

Dental

Vision

401k