01
Public GitHub repositoryFHIR Medication Safety Intelligence
Connect standards-based healthcare data with medication safety analysis using FHIR.
Technology leadership / Applied AI
Leading technology.
Building what’s next.
I’m Srini Venkataraman. I bring together technology leadership, enterprise architecture, and software engineering to turn complex business problems into practical technology solutions. My work spans enterprise applications, data platforms, and applied AI.
Selected work
From architecture
to working solutions.
Three projects exploring medication safety, healthcare interoperability, and energy analytics. Explore each project’s purpose, architecture, and technical approach, with source code available on GitHub.
02
Public GitHub repositoryMedication Safety Agent
Analyze medication and lab data to identify potential safety concerns and provide traceable explanations.
03
Public GitHub repositoryEnergy Customer Insights
Explain changes in electricity usage through data analysis, weather context, and AI-assisted insights.
About me
Technology leadership.
Engineering breadth.
My experience spans enterprise application development, architecture, engineering leadership, and technology strategy. I’ve led engineering teams, worked alongside data and analytics professionals, and guided software initiatives from planning and design through delivery and ongoing support.
I take a technology-agnostic approach, choosing tools and platforms that address business needs while aligning with enterprise standards and existing systems. Alongside my advisory work at Open Sky Health, I stay actively involved in hands-on development, building projects in data engineering, cloud platforms, and applied AI. This work keeps me learning and informs how I approach architecture and technology decisions.
Open Sky Health
Co-Founder & Technology and Product Advisor
April 2018–Present
Guide product strategy, architecture, and implementation planning, connecting business needs with technology decisions.
UAB Medicine
Director of Application Development
April 2001–April 2024
Led engineering teams and directed enterprise application development, systems integration, and modernization across hospital and ambulatory settings.
12+ enterprise applications · 30+ EHR enhancements · 10,000+ users supported
Education
Business and technology
MBA, University of Alabama at Birmingham
Master of Computer Applications, Bharathidasan University
BSc in Chemistry, Bharathidasan University
Career impact
Technology at operational scale.
Led and directed application development supporting 10,000+ users across hospital and ambulatory settings during my tenure at UAB Medicine.
12+Enterprise applications
Application development, integration, and modernization
30+EHR enhancements
Improved information access and clinician workflows
10+Mobile & outreach applications
Connections with consumers, external providers, and external organizations
1,400+Providers
Adoption of a mobile EMR application
400K+Annual eSignatures
iPad surgical-consent platform
288K+Annual delivery events
Integrated medical-device delivery platform
Selected accomplishments during my UAB Medicine tenure. Application categories may overlap.
Expertise
Strategy, architecture, and delivery.
Leadership & delivery
Engineering leadership, team development, product and technology strategy, stakeholder alignment, architecture governance, and Agile delivery.
Applications & integration
Enterprise architecture, application modernization, APIs, and systems integration. Java, Spring Boot, React, React Native, RabbitMQ, HL7/FHIR, AWS HealthLake, and Oracle Health/Cerner integration.
Data & applied AI
Data engineering, analytics, cloud data platforms, and AI-assisted explanations grounded in source data. Python, SQL, Databricks, Unity Catalog, MLflow, and Amazon S3.
Engineering practice
Secure development, maintainable software, automated testing, and reliable delivery through DevOps and CI/CD.
What comes next
Expanding into AI search
and document intelligence.
My next projects will explore how vector search and retrieval-augmented generation (RAG) can turn unstructured documents into useful insights, with answers linked to supporting sources.
Research & planned projects
Healthcare document intelligence: Explore retrieval across synthetic hospital notes to surface information relevant to a patient’s symptoms or diagnoses, with source-linked explanations.
Energy & utility AI search: Explore document ingestion, semantic search, and grounded answers across utility documents, extending the Energy Customer Insights portfolio.
Explore my GitHub →