The Team:The Digital Technology Services Leadership(DTS)team is a fast-paced energetic and high-performing team at the heart of S&P Globalin the Digital Solutions organization. DTS provides services across a broad range of technical disciplines and leverages investment in world-class technologies in support of S&PGlobalsproducts and clients.The Head of AI and Automation Architecturewill partner closely with the Enterprise Program Management Enterprise Architectureand DTS product teamstoarchitect and redesign core business systems and processes.

Responsibilities and Impact:

1. AI & Agentic Systems Strategy

• Establish enterprise-wide AI and agentic systems architecture standards reusable patterns and reference models.

• Define the reference architecture for deploying Autonomous Agents and Multi-Agent Systems (MAS) within the enterprise infrastructure.

• Architect endtoend model lifecycle platformsincluding training evaluation deployment and monitoringand integrate with enterpriseMLOps/AIOps capabilities.

• Lead the transition from deterministic RPA (task automation) to probabilistic reasoning-based Agentic workflows.

• Work with theEnterprise Agent Framework (EAF)initiative toestablishgovernance guardrails and human-in-the-loop protocols for autonomous system decision-making.

• Partner with InfoSec to embed AIspecific risk management zerotrust patterns and regulatory compliance into all automation and agentic workflows.

• Define standards for model selection (LLM vs. SLM) retrieval augmentation vector indexing and toolcalling frameworks

2. Process Re-Engineering & Optimization

• Partner withEnterprise Program Management Office (EPMO)COE and business stakeholders to deconstruct legacy workflowsidentifyingbottlenecks that require architectural redesign rather than simple digitization.

• Apply systems thinking to simplifyand synthesizeprocesses before automating them ensuring we do not automate inefficiency.

• Create aprocess digital twincapability to simulate workflow changes before production deployment.

3. Automation & Orchestration Architecture

• Own thearchitecture fortechnology stack for hyper-automation (e.g. RPA platforms Orchestrators iPaaS and Vector Databases).

• Design the integration layer that allows AI Agents to securely interact with core systems of record (ERP CRM ITSM).

• Oversee the Automation Center of Excellence (CoE) strategy setting standards for code reusability and bot lifecycle management.

4. Leadership & Evangelism

• Lead a specialized team of solution architects and engineers.

• Act as the primary liaison between the DTS and DS groupsEPMO /Transformation office and key business stakeholders translating complex AI and automation capabilities into tangible ROI.

Compensation/Benefits Information:

(This section is only applicable to US candidates) S&P Globalstatesthat theanticipatedbase salary range for this position is $185000 to $ salary for this role will be based on the individuals geographic location as well as experience level skill set traininglicensesand certifications.

In addition to base compensation this role is eligible for an annual incentive plan. This role is not eligible foradditionalcompensation such as an annual incentive bonus or sales commission plan. This role is eligible to receiveadditionalS&P Global benefits. For more information on the benefits we provide to our employees please clickhere.

What Were Looking For:

Basic Required Qualifications:

• Bachelors degree in Computer Science Engineering or related technical field or equivalent work experience

• 7 years of software development experience with proven leadership and team management skills

• Strongproficiencywith modern LLM/SLM ecosystems vector retrieval architectures semantic search and toolcalling/agent frameworks.

• Strongproficiencyin programming languages such as Java Python C# or JavaScript

• Extensive experience with workflow engines eventdriven architectures distributed systems design and enterprise integration patterns.

• Experience with cloud platforms such as AWS AzureandGoogle Cloud Platform includingleadership designing cloudscale AI inference architectures (GPU/accelerator workloads Kubernetesbased model serving)

• Demonstrated success influencing executives engineering leaders and crossfunctional teams in complex multistakeholder environments.

• Solid understanding of software architecture patterns microservices and distributed systems

• Experience with agile development methodologies and DevOps practices

Additional Preferred Qualifications:

• Experience leading engineering teams in financial services or data-driven organizations

• Strong grounding in enterprise security architecture: zero trust identityaware agents policy engines model risk frameworks

• Familiarity with CI/CDand developmentplatformsincluding but not limited to JenkinsGitHub or Azure DevOps

• Abilityto translate ambiguous business problems into scalable AInative architectural strategies.

• Strong communicationskills with ability to present technical concepts to both technical and non-technical stakeholders