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 end‑to‑end model lifecycle platforms—including training, evaluation, deployment, and monitoring—and integrate with enterprise MLOps/AIOps capabilities.
Lead the transition from deterministic RPA (task automation) to probabilistic, reasoning-based Agentic workflows.
Work with the Enterprise Agent Framework (EAF) initiative to establish governance, guardrails, and "human-in-the-loop" protocols for autonomous system decision-making.
Partner with InfoSec to embed AI‑specific risk management, zero‑trust patterns, and regulatory compliance into all automation and agentic workflows.
Define standards for model selection (LLM vs. SLM), retrieval augmentation, vector indexing, and tool‑calling frameworks.
Partner with Enterprise Program Management Office (EPMO) COE and business stakeholders to deconstruct legacy workflows, identifying bottlenecks that require architectural redesign rather than simple digitization.
Apply systems thinking to simplify and synthesize processes before automating them, ensuring we do not automate inefficiency.
Create a process ‘digital twin’ capability to simulate workflow changes before production deployment.
Own the architecture for technology 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.
Lead a specialized team of solution architects and engineers.
Act as the primary liaison between the DTS and DS groups, EPMO/Transformation office, and key business stakeholders, translating complex AI and automation capabilities into tangible ROI.

Requirements

Bachelor's 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
Strong proficiency with modern LLM/SLM ecosystems, vector retrieval architectures, semantic search, and tool‑calling/agent frameworks.
Strong proficiency in programming languages such as Java, Python, C#, or JavaScript
Extensive experience with workflow engines, event‑driven architectures, distributed systems design, and enterprise integration patterns.
Experience with cloud platforms such as AWS, Azure, and Google Cloud Platform, including leadership designing cloud‑scale AI inference architectures (GPU/accelerator workloads, Kubernetes‑based model serving)
Demonstrated success influencing executives, engineering leaders, and cross‑functional teams in complex, multi‑stakeholder environments.
Solid understanding of software architecture patterns, microservices, and distributed systems
Experience with agile development methodologies and DevOps practices.

Benefits

Health & Wellness: Health care coverage designed for the mind and body.
Flexible Downtime: Generous time off helps keep you energized for your time on.
Continuous Learning: Access a wealth of resources to grow your career and learn valuable new skills.
Invest in Your Future: Secure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs.
Family Friendly Perks: It’s not just about you. S&P Global has perks for your partners and little ones, too, with some best-in class benefits for families.
Beyond the Basics: From retail discounts to referral incentive awards—small perks can make a big difference.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

AI architectureMulti-Agent SystemsMLOpsAIOpsRPALLMSLMvector retrievalprogramming languagescloud-scale AI inference

Soft Skills

leadershipteam managementinfluencingcommunicationsystems thinking