Ade Adeoshun

IT executive with 20+ years in Network, Cyber Security, Telecommunication and now turning machine learning research into production systems that move revenue, cost and risk metrics. Built and led AI organizations of up to 25 scientists and engineers across three continents, with annual budgets above $80M. Delivered $3.5B+ in cumulative business impact through recommendation, forecasting, NLP and generative AI programs.

Known for pairing technical depth with board-level communication, responsible AI governance and a strong record of hiring and growing senior talent.

Ai Advisor: Ai Roadmap, Ai Adoption, and Cloud Tech — Principal a Delivery Lead, Ai Advisor across a $40M technology portfolio. at Delegates Group Corporation | Client: Florida Department of Agriculture & Consumer Services (FDACS) (2025-06 – Present)

• AI strategy: Architected the enterprise AI roadmap and governance model (AI review board, risk tiers, acceptable-use policy) linking internal databases to approved external LLMs through a secure gateway with redaction and audit logging.
• LLM & agent orchestration: Built a retrieval-augmented generation (RAG) and tool-use layer over agency policy, licensing and inspection records, orchestrating multi-step agents that retrieve, call system-of-record APIs, draft and route for human approval; prompt engineering and parameter-efficient fine-tuning on agency terminology raised answer accuracy from 71% to 92% on a curated evaluation set.
• Agent assist & automated resolution: Delivered an agent-assist copilot for the consumer services contact center (real-time policy answers, case summaries, next-best actions) plus automated resolution of routine license and complaint-status requests, deflecting 30% of tier-1 contacts and cutting average handle time 22%.
• AI platform enablement: Stood up a shared AI platform (LLM gateway, prompt and evaluation library, reusable data connectors) serving 5 divisions and 8 product teams, cutting time-to-pilot for new AI use cases from months to under 4 weeks.
• Cloud: Designed scalable Azure and Oracle Cloud (OCI) infrastructure, speeding service delivery 35%.
• Network refresh: Led an $8M infrastructure refresh from Cisco to Extreme Networks, modernizing the enterprise network for cloud and AI workloads.
• Vendor management: Renegotiated IT service contracts, saving 15% (about $1.2M) a year.
• Security & compliance: Directed enterprise-wide security audits that raised compliance adherence 25%.
• Delivery: Aligned multiple teams around one operating cadence, cutting project lead times 20%.

Principal Delivery Lead (artificial intelligence for Customer Journey) at Infosys Ltd & Infosys Public Ltd: Google Alphabet, Aerojet Rocketdyne/L3Harris, ADP (2024-01 – 2025-06)

Led 200+ engineers across 3 continents supporting tiered clients; accountable for a $1.4B annual managed-services portfolio.

• MSP transitions: Ran RFP/RFQ and transition programs moving multiple clients and service towers from incumbent providers to Infosys, covering $120M in total contract value without service disruption.
• Operational excellence: Introduced proactive maintenance and automated monitoring for Level 3–5 incidents, reducing outages 40% over two years.
• AIOps automated resolution: Shipped agent-assist and automated-resolution workflows for the Level 3–5 service desk: LLM ticket summarization, embedding-based similar-incident retrieval and runbook automation that auto-resolved 35% of recurring incidents and cut mean time to resolve 30%.
• MLOps: Standardized the model lifecycle on Vertex AI and SageMaker with MLflow experiment tracking, Kubeflow pipelines, a central model registry and CI/CD release gates, taking models from notebook to production in days instead of weeks.
• Model monitoring & experimentation: Implemented production monitoring (data drift, latency, roundedness’ and hallucination rates), offline evaluation suites and A/B online experiments, with agent thumbs-up/down feedback loops feeding monthly retraining, lifting first-contact resolution 18%.
• Platform & enablement: Ran a central AI/ML platform team supporting 12 product and service-tower teams across client accounts with shared templates, feature pipelines and guardrails, so teams launched ML features without rebuilding infrastructure.
• Cybersecurity: Rolled out new security practices across client estates, cutting security breaches 60%.
• Business alignment: Led organization-wide IT strategy sessions that tied technology plans to client objectives, raising service reliability 28%.
• Delivered a $10M infrastructure refresh that increased output capacity 25% within budget.
• Proved ROI on Ai
• Set a baseline before go-live to measure denial rate, prior-auth turnaround, after-hours minutes, overtime.
• Define the target in the business case, measure at 90 days & 12 months, and report on value dashboard to the CIO.
• Count hard dollars (revenue recovered, agency spend avoided) separately from capacity

Principal Delivery Manager at Infosys Ltd: Cisco Systems, Verizon, Allison Transmission Indiana, Molina HealthCare, Fidelity Insurance (2015-12 – 2024-01)

• Defined and executed a three-year AI roadmap adopted by the executive committee, growing AI-driven revenue from $12M to $95M annually.
• Launched the company's first generative AI platform, serving 18,000 employees and cutting average customer-service handle time by 32%.
• Built a real-time fraud detection system processing 40M transactions per day, reducing fraud losses by $48M per year.
• Established a Responsible AI Council and model risk framework aligned with NIST AI RMF, passing every regulatory audit since inception.
• Consolidated four ML platforms into one MLOps stack, cutting model deployment time from 9 weeks to 6 days and infrastructure cost by 28%.
• Grew the team from 22 to 85, promoting 14 people into senior and principal roles; held annual attrition below 8%.
• Mentored 128 data scientists, ML engineers, analysts and software engineers on applied ML practice (feature engineering, experiment design, model evaluation, MLOps), with 30 promoted to senior roles; ran weekly design reviews and an internal AI guild of 260+ members.
• Designed and shipped LLM-powered clinical documentation and scheduling assistants using RAG over 5M+ records, improving staff productivity by 30% across pilot clinics.
• Led a squad of 6 engineers in migrating batch ML pipelines to a real-time streaming architecture on AWS, cutting data latency from hours to under 90 seconds.
• Implemented MLOps practices on MLflow and Kubeflow (model registry, canary deployments, drift monitoring) that raised model deployment frequency by 4x with zero Sev-1 incidents.
• Partnered with product and compliance teams to ensure HIPAA-aligned data handling and explainability for all AI features.
• Reviewed 1,000+ pull requests and authored the team's coding, testing, and API design guidelines.
• Built Java and Python microservices and REST APIs supporting route optimization and shipment tracking for 400+ enterprise customers.
• Developed an ML-based demand-forecasting service that improved delivery-window accuracy by 18%.
• Latent factor modeling: Built a matrix factorization (ALS) and embedding-based recommendation engine for ADP’s HR and payroll self-service portal, modeling latent employee–content fact

MBA

BSc