AKINDOYIN Akinbiyi, PhD

Led multi-stakeholder technical engagements across architecture, build planning, integration, and go-live readiness, aligning engineering, product, and business leaders to achieve strategic delivery and technical requirements.

Developed comprehensive reference architectures, decision records, and implementation roadmaps, accelerating secure cloud platform adoption and distributed application patterns.

Managed end-to-end customer lifecycle, leading multi-disciplinary engagements from discovery to production cutover, resolving critical issues and driving feature discussions.

Designed and deployed large-scale GPU clusters for training and inference, delivering hardened reference designs with robust capacity planning, HA, and operational runbooks.

Standardized production serving patterns using NVIDIA stack (Triton, TensorRT-LLM, CUDA-X), operationalizing GPU telemetry with DCGM dashboards and alerts.

Optimized distributed training performance by tuning NCCL and topology-aware configurations, resolving critical bottlenecks across network, storage, and framework layers.

Co-developed partner-ready solution kits, including sizing guides, Terraform modules, and validation playbooks, accelerating solution adoption and consumption.

Led cloud security architecture for a multi-region data lakehouse platform, ensuring compliance with NIST 800-53, PCI-DSS, and GDPR.

Converted successful LLM fine-tuning and inference PoCs into production deployments, incorporating robust security controls, SLAs, and runbooks.

Implemented LoRA/QLORA pipelines and integrated model stacks with NeMo for enterprise RAG, enhancing model fine-tuning and deployment workflows.

Deployed and optimized GPU workloads across Kubernetes and SLURM, configuring scheduling, quotas, and multi-tenant controls for enterprise developer teams.

Established and executed benchmark methodology for training/inference throughput, identifying and resolving scaling bottlenecks through load tests and profiling.

Enabled enterprise developers by authoring tutorials, "golden path" templates, and reference repositories, significantly unblocking adoption.

Secured AWS infrastructure for forecasting and optimization workloads by defining robust VPC architectures, private subnets, security groups, and private link endpoints.

Designed and built secure, scalable multi-region architectures with network segmentation, IAM, encryption, and audit logging for high-throughput workloads.

Delivered IaC-based cluster provisioning and standardized environments, implementing policy guardrails and operational readiness checks.

Enhanced platform stability by establishing SLOs, telemetry, incident playbooks, and capacity forecasting, leading to proactive monitoring and automated remediation.

Automated security workflows using AWS Lambda and Step Functions, remediating open security groups, unencrypted S3 buckets, and non-compliant IAM policies.

Integrated vulnerability findings and misconfiguration alerts into ServiceNow, streamlining end-to-end remediation workflows with operations teams.

Authored high-quality architecture diagrams, runbooks, and security playbooks, enhancing incident response and operational procedures in a remote-first environment.

Defined strategic roadmaps and influenced investment prioritization for public cloud adoption, guiding strategy and design.

Conducted regular vulnerability assessments, ensuring compliance with SOC2, ISO 27001, and other regulatory requirements.

Played a pivotal role in incident response, leveraging Prisma Cloud to rapidly identify and remediate security incidents in the cloud.

Maintained the enterprise architecture repository, ensuring consolidation and accuracy of various teams' architectural artifacts.

Triaged large programs of work to identify broad enterprise architecture impact and effort.

Reviewed and assisted teams and line architects in aligning and cohesive local architecture strategies and roadmaps.

Developed and designed cloud security patterns, enabling seamless migration of workloads to public cloud for cross-functional teams.

Developed proofs of concept for automations, enabling cloud-native services compliant with security, operational, and financial best practices.

Implemented DevOps practices, including IaC (Terraform, CloudFormation), CI/CD, and automated deployment.

Deployed Kubernetes container orchestration on AWS EKS and GCP GKE.

Implemented and managed continuous integration and delivery systems and methodologies.

Implemented and automated security controls, governance processes, and compliance frameworks/validation.

Provided technical input and expertise to architecture governance processes for new GCP and AWS cloud services.

Defined and deployed comprehensive monitoring, metrics, and logging cloud systems.

Implemented highly available, scalable, and self-healing systems for digital cloud data platforms, aligning with global blueprints (AWS and GCP WAF policies).

Delivered multiple production products, including NodeJS application migration to AWS, Container Scanning Solution, Service Hosted Platform, Automated AMI Bakery, and Digital Splunk on AWS.

Presented product solutions at KubeSec Europe 2020, showcasing expertise in cloud security and platforms.

Documented program-level design decisions and open items, enhancing transparency and alignment with key stakeholders.

Collaborated with cross-functional teams (Platform, Cloud, Security, Architecture), ensuring project deadlines and business requirements were consistently met.

Led internal and external projects, developing solutions for document/text ingestion, NLP/NLG, knowledge representation, and automated report generation.

Applied supervised and unsupervised machine learning methods to solve complex analytical problems.

Built and automated consistent AWS infrastructure solutions, distributing them across multiple project accounts.

Developed architecture blueprints and detailed documentation, including Service Catalog and bills of materials for AWS services (EC2, S3).

Created and promoted cloud security best practice blueprints, ensuring alignment and compliance with the cloud security team.

Built new SharePoint sites and Microsoft Teams to meet diverse customer requirements.

Supported and administered SharePoint (on-premise and online) and O365, including Teams and Office Apps.

Designed and executed comprehensive cloud migration strategies, including delivery architecture, migration plans, orchestration, and runbooks.

Identified and evangelized appropriate AWS and GCP architectural best practices across projects.

Designed and deployed scalable, highly available, and resilient solutions on GCP and AWS.

Mapped business requirements to technical solutions, developing business cases to capture ROI and cost implications.

Created and maintained optimal AWS data pipelines using Python.

Utilized a wide array of cloud big data tools, including AWS Lambda, EMR, Redshift, and SageMaker, for data processing.

Developed and trained machine learning models using AWS SageMaker.

Built infrastructure for optimal ETL from diverse data sources using SQL and AWS big data technologies.

Identified, designed, and implemented internal process improvements, automating manual processes and optimizing data delivery for scalability.

Automated EC2 AMI generation/deletion and provisioned lifecycle policies for S3 and AWS RDS.

Integrated AWS RDS (PostgreSQL) with MS Power BI to build analytics tools for actionable data insights.

Collaborated with market risk managers to test and validate models, facilitating independent review processes for CSDR.

Conducted regulatory analysis on market risk models using Python for CSDR implementation.

Supported risk managers in understanding model behavior and impact on specific portfolios.

Developed models (Excel, VBA, Access, SQL) to estimate P&L impact of T2S and buy-in penalties for CSDR implementation.

Developed and implemented an FRTB risk calculations framework, including models, calculation modules, and data analysis tools (Qlik, Alteryx, Tableau).

Designed and implemented a BluePrism RPA Proof of Concept to automate invoice statement generation, consolidating data from 5 disparate systems and applying logical business rules.