Engineering Leader | Technical Manager | 12 Years Experience
Technical Lead to Engineering Management | Building AI Systems at Scale4-app AI platform • 100% local • Privacy-focused
Privacy-focused AI platform with Personal AI Assistant (multi-model chat & image generation), Code Documentation Generator (auto-docs for any codebase), Local RAG System (semantic search with citations), and AI Image Classifier (auto-tagging & face recognition).
Engineering Leader with 12+ years of experience leading technical teams and building production systems at scale. Currently managing 8-15 engineer cross-functional team at STERIS ($3B revenue, 17K employees), achieving 90% retention rate through mentorship and career development. Acted as Engineering Manager during leadership transitions, reporting directly to VP and executive leadership, making hiring decisions, allocating engineering resources, and driving technical strategy. Built backend supporting 50K+ daily users with 99.95% uptime across 500+ enterprise installations. Deep expertise in AI/ML infrastructure, having built production multi-agent systems, RAG platforms, and LLM evaluation frameworks. Seeking Engineering Manager role where I can apply proven leadership experience, team development track record, and passion for building high-performing engineering organizations.
STERIS CORP • Dec 2021 - Present
8 Direct Reports | Interim Engineering Manager
• Lead cross-functional team of 8 engineers with 90% retention rate
• Streamlined compilation for 100+ Red Hat packages, reducing build time by 40%
• Delivered 15+ major feature releases including internationalization for 4 markets
• Mentored 10+ engineers in modern development practices, improving team productivity
• Managed team priorities during leadership transitions as interim manager
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Privacy-focused 4-app AI platform: Personal AI Assistant (multi-model chat & image generation), Code Documentation Generator (auto-docs for any codebase), Local RAG System (semantic search with citations), and AI Image Classifier (auto-tagging & face recognition). 100% local, fully containerized. Demonstrates production-ready AI architecture with real-world applicability for enterprise privacy requirements.
Framework for evaluating LLM outputs with LLM-as-judge pattern, consistency testing, and RAG evaluation. Includes 6 evaluators (Accuracy, Consistency, Latency, Cost, LLM-as-Judge, RAG), multi-provider runners (Ollama, OpenAI, Anthropic), and CLI for automated testing. Addresses critical production AI challenge: measuring LLM performance at scale. Used for real-world model selection and optimization workflows.
Lightweight observability layer for AI/LLM applications. Decorator-based tracing (@trace, @trace_workflow), web dashboard with timeline visualization, and framework integrations for Ollama, CrewAI, and LangChain. SQLite/PostgreSQL storage.
Complete Arch Linux setup with GNOME for Microsoft Surface Pro devices. Includes custom kernel patches, hardware optimization scripts, and configuration for touch/stylus support. Addresses Surface-specific challenges like firmware, battery management, and type cover integration.
Chrome extension for exporting Claude AI conversations to markdown, JSON, or text format. Built to preserve important AI interactions for documentation and knowledge management workflows.
Developer-focused tab management Chrome extension for organizing browser sessions, saving workspace states, and quickly restoring development environments. Reduces context-switching overhead for multi-project workflows.
Chrome extension that converts web page selections to clean markdown format. Preserves formatting, links, and code blocks for seamless documentation workflows.
Personal journaling application with stylus and touch support for natural writing experience. Features daily entries, mood tracking, and searchable history for mindful reflection and personal growth.
Engineering Leader | Technical Manager | 12 Years Experience
shalin.dev@proton.me | 415-490-7852 | San Francisco Bay Area
shalinbhatt.dev | github.com/shalin-dev | linkedin.com/in/shalinkb
Privacy-focused 4-app AI platform: Personal AI Assistant (multi-model chat & image generation), Code Documentation Generator (auto-docs for any codebase), Local RAG System (semantic search with citations), and AI Image Classifier (auto-tagging & face recognition). 100% local, fully containerized. Demonstrates production-ready AI architecture with real-world applicability for enterprise privacy requirements.
Framework for evaluating LLM outputs with LLM-as-judge pattern, consistency testing, and RAG evaluation. Includes 6 evaluators (Accuracy, Consistency, Latency, Cost, LLM-as-Judge, RAG), multi-provider runners (Ollama, OpenAI, Anthropic), and CLI for automated testing. Addresses critical production AI challenge: measuring LLM performance at scale. Used for real-world model selection and optimization workflows.
Lightweight observability layer for AI/LLM applications. Decorator-based tracing (@trace, @trace_workflow), web dashboard with timeline visualization, and framework integrations for Ollama, CrewAI, and LangChain. SQLite/PostgreSQL storage.
San Francisco, CA
Engineering Leadership & People Management
Technical Architecture & Platform Strategy
Developer Tools & Platform Engineering
Cross-Functional Leadership & Stakeholder Management
Tech: Ruby on Rails, GraphQL, MySQL, PostgreSQL, JavaScript, Vue.js, Docker, Jenkins, Linux
San Francisco, CA
Technical Leadership & Team Development
Technical Contributions
Process Improvement & Scrum Leadership
Tech: Ruby on Rails, MySQL, PostgreSQL, JavaScript, jQuery, CSS, Docker, Jenkins, Kubernetes, Linux