Capital Group is looking to establish an enterprise AI platform to accelerate innovation while meeting rigorous standards for security, compliance, and operational excellence. The goal is to turn cutting-edge AI into measurable business value by governing responsibly and optimizing for speed, reliability, cost, and ROI.
Requirements
- You have 10+ years of experience designing and implementing complex distributed systems and enterprise architectures, with a proven track record of building scalable, resilient platforms.
- You have 5+ years of experience operating public and private clouds (AWS, Azure), leveraging cloud-native services, containers (Docker/Kubernetes), and serverless technologies, with exposure to hybrid or multi-cloud environments.
- You bring strong software engineering foundations (10+ years), including coding, APIs, integration patterns, and maintainable design, with proficiency in languages such as Python, Java, or Go.
- You are skilled in building automated CI/CD pipelines (e.g., GitHub/GitLab, Jenkins), implementing Infrastructure as Code (Terraform, CloudFormation), and embedding DevSecOps controls in the path to production.
- You have 5+ years of experience applying application and infrastructure security—including IAM, network security, encryption/tokenization—and operating against compliance frameworks such as SOC 2 and GDPR.
- You demonstrate a solid understanding of AI, large language models, and end-to-end ML workflows (training, fine-tuning, inference), with hands-on MLOps and production model deployment experience.
- You are adept at troubleshooting complex cross-stack issues using data and telemetry and driving timely resolution.
Responsibilities
- Define and Execute Platform Strategy: You will set the vision, roadmap, and operating model for Capital’s Custom Development AI platform, aligning with enterprise architecture and business goals while balancing speed, scale, and governance.
- Build and Evolve AI Capabilities: You will lead the design, development, and deployment of scalable, reusable AI services—covering model serving, orchestration, guardrails, and developer enablement through SDKs, APIs, and CI/CD pipelines.
- Ensure Security, Compliance, and Responsible AI: You will embed security, privacy, and ethical guardrails into all layers of the platform, enforce governance standards, and partner with InfoSec and risk teams to meet regulatory and policy requirements.
- Drive Operational Excellence and Reliability: You will establish SRE principles, observability, FinOps practices, and service management processes that ensure high availability, cost efficiency, and resilience of AI services.
- Lead Cross-Functional Collaboration and Team Development: You will partner with product, architecture, and security teams to deliver enterprise-ready AI solutions, while mentoring and growing an inclusive, high-performing platform engineering team.
- architect secure, scalable, and resilient foundations that accelerate innovation while meeting rigorous standards for security, compliance, and operational excellence.
- own the end-to-end design, delivery, and evolution of a secure, scalable platform that empowers teams across the organization to build and deploy AI applications at scale.
Other
- Lead by example—mentoring engineers, guiding cross-functional initiatives, and fostering a collaborative, inclusive culture.
- Communicate complex technical concepts clearly to non-technical stakeholders and executives, producing well-structured proposals, architectural diagrams, and documentation.
- You have experience operating in large, regulated enterprises (ideally financial services), and navigating governance, risk, and compliance when introducing new technologies like AI.
- You are comfortable working with ITSM tools and frameworks (e.g., ServiceNow, ITIL) and integrating automated workflows for incident and change management.
- You demonstrate mastery of Agile delivery (Scrum/Kanban) and DevSecOps practices, embedding security throughout the SDLC.
