About this role
Global role to shape, drive, and execute SSIM's Analytics and AI strategy, overseeing platform engineering, software engineering, ML/LLM Ops, and governance to support the COO organization globally.
Key Responsibilities
- Lead end-to-end implementation of platform infrastructure, software applications, foundational data science capabilities, advanced analytics and AI frameworks, tooling, ML/LLM Ops, and Model Observability
- Define Analytics and AI Platform architecture; establish engineering standards; guide implementation and governance
- Ensure modular, scalable architecture; champion engineering excellence
- Manage major vendor relationships with analytics and AI platform providers
- Oversee deployment across sandbox, development, QA/UAT, production, to disaster recovery
Technical Overview
Leadership of analytics and AI infrastructure across cloud, GPU/TPU, AI frameworks, GenAI/Agentic AI integration; focus on IAC, ML/LLM Ops, FinOps, model observability, security, and disaster recovery.
Ideal Candidate
The ideal candidate is an executive-level platform engineering leader with 15+ years building analytics/AI platforms at scale, strong cloud and AI infra expertise, and demonstrated experience leading global teams and vendor partnerships in financial services.
Must-Have Skills
Master's degree required (Computer ScienceElectrical Engineering or related field)15+ years in core engineering role at large enterprise15+ years hands-on engineering experience delivering analytics and/or AI solutions and platformsProven experience leading global technology organizations across infrastructureIACML/LLM Opsanalytics and AI frameworks/toolsFinOpshigh availability and disaster recoveryStrong understanding of the analytics and AI vendor landscape and demonstrated experience adopting vendor products and opensource frameworks to improve scale and growthFluent in English; highly detailorientedresultsdrivencandidand executionfocused
Nice-to-Have Skills
Prior AI platform engineering leadership experience in large financial institutionCFA Level I or equivalent credential
Tools & Platforms
TerraformKubernetesCUDAGPU
Required Skills
Master's degree required (Computer ScienceElectrical Engineering or related field); 15+ years in core engineering role at large enterprise; 15+ years hands-on engineering experience delivering analytics and/or AI solutions and platforms; Proven experience leading global technology organizations across infrastructureIACML/LLM Opsanalytics and AI frameworks/toolsFinOpshigh availability and disaster recovery; Strong understanding of the analytics and AI vendor landscape and demonstrated experience adopting vendor products and opensource frameworks to improve scale and growth; Fluent in English; highly detailorientedresultsdrivencandidand executionfocused
Hard Skills
ML/LLM OpsGenAIAgentic AIModel ObservabilityInfrastructure as CodeIACTerraformKubernetesCUDAGPUTPUFPGACloud ComputingFinOpsData governanceVendor managementSecurity & ComplianceDisaster recoveryAI frameworksGenAI/Agentic AI integration protocols/frameworksCloud Computing/Agnostic
Soft Skills
LeadershipStakeholder managementCommunicationStrategic thinkingRelationship buildingCross-functional collaborationExecution focusMentoringOperational excellence
Certifications
Preferred
CFA Level I or equivalent credential
Keywords for Your Resume
Global Head of Analytics and AI Platform EngineeringManaging DirectorAnalytics and AI PlatformPlatform engineeringML/LLM OpsGenAIAgentic AIModel ObservabilityInfrastructure as CodeIACTerraformKubernetesCUDAGPUFinOpsData governanceVendor managementLeadershipEnglishState StreetSSIMcloud computingAI frameworksplatform engineeringml/llm opsgenerative aiagentic aimodel observabilityinfrastructure as codeterraformkubernetescudagpu
Deal Breakers
Master's degree not held, Less than 15 years in core engineering, Lack of hands-on AI platform leadership experience in financial services
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