Short bio
I am a technical leader and problem solver who designs and delivers scalable, distributed software and AI systems that create measurable business value. I have led cross-functional teams and platform initiatives, translating complex requirements into reliable, production-ready solutions built on open standards. My experience spans architecting, mentoring, and driving execution across diverse technology stacks, with a strong focus on operational excellence, product impact, and long-term system sustainability.
Tech stack
Work experience
- Snr. Staff Software Engineer02/26 – 07/265 m.
Spearheaded AI-driven automation across a large OB/GYN practice by developing an AI phone agent that manages patient calls, schedules appointments, and seamlessly integrates VoIP and EHR systems to streamline clinical operations.
Responsibilities:- Architected and led the development of an end-to-end AI-powered medical imaging platform, enabling ultrasound data capture, cloud-based processing, and analysis for remote, low-resource healthcare environments.
- Designed and deployed scalable cloud infrastructure on AWS using S3, Lambda, CDK, SQS, and CloudWatch to power AI workflows, medical imaging pipelines, and healthcare automation services.
- Machine Learning Engineer, AI as a Service (AIaS)07/21 – 10/254 y.
Led cross-functional efforts to scale a company’s AI-as-a-Service (AIaS) platform, enabling rapid, compliant deployment of ML models across high-volume fraud detection, credit risk, and analytics pipelines processing billions of transactions daily.
Responsibilities:- Built and optimized low-latency inference microservices serving a company’s enterprise AI models, deployed across GCP, AWS, Azure and on-prem, achieving strict SLA compliance and delivering real-time insights with sub-second latency.
- Led design and deployment of RAG based AI solutions over internal knowledge systems, implementing robust guardrails and validation frameworks to ensure compliant, secure, and reliable LLM outputs in production.
- Designed and automated end-to-end MLOps pipelines (Airflow, PySpark, Kubernetes) for model retraining, monitoring, and CI/CD, reducing update latency and improving reliability for large-scale AI workloads.
- Mentored engineers on scalable ML deployment, reproducibility, and observability, fostering technical excellence and operational maturity across global AI platform teams.
- Owned end-to-end model release lifecycle, from validation and staging to canary deployment, monitoring, and rollback, ensuring reliable, compliant production rollouts at scale.
- Machine Learning Engineer, a company Watson08/19 – 06/212 y.
Owned end-to-end enhancements to Watson’s Visual Recognition APIs on a company Cloud, improving scalability, reliability, and model performance for enterprise clients.
Responsibilities:- Led cross-team collaboration to deliver cloud-based cognitive solutions, mentoring junior engineers in ML model development and deployment best practices.
- Accelerated delivery of AI solutions by leveraging and extending a company Cloud frameworks, streamlining cognitive model lifecycle management.
- Implemented a face similarity search API leveraging indexed face feature embeddings.
- Senior Software Developer09/11 – 08/165 y.
Engineered enterprise software integrations, APIs, web-apps, and resolved issues around availability and performance for this major African technology services company’s robust messaging systems and SOA infrastructure.
Responsibilities:- Oversaw development of online banking platform for Fidelity Bank using JBoss Fuse ESB & components, Elasticsearch (ELK), MSSQL and Redis; this resulted in attracting many customers and significantly increasing revenues for this client.
- Championed developer experience initiatives, leading the creation of the Interswitch Developer Console and onboarding programs that empowered partner engineers and accelerated API adoption across key financial institutions.
