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Aniruddha Rajnekar
Mid-level Full-Stack Engineer specializing in FinTech and cloud-native systems
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About
Full-stack engineer with about 3 years of experience who is deeply hands-on with AI-assisted development and agentic systems. Built TubeAgent using LangChain, Ollama, FAISS, and Llama 3, and has demonstrated measurable impact by cutting review time by 90% and reducing deployment time from 30 minutes to under 5 minutes at NC State. Combines practical experimentation with strong architectural thinking around resilient, composable AI systems.
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Key Strengths
- AI-accelerated full-stack development workflow
- Built TubeAgent autonomous agentic AI system
- Strong RAG pipeline and LangChain architecture experience
- Reduced technical content review time by 90%
- Optimized Docker and AWS CI/CD deployments from 30 minutes to under 5 minutes
- Designs resilient systems with clean interfaces and circuit breaker patterns
- Tech lead ownership from architecture specification through failure mitigation
- Hands-on, rapid prototyping approach to evaluating new AI tools
Reference Highlights
- strong ownership of reliability
- proactive post-launch iteration
- strong end-to-end execution
- delivered complete AI workflow
- improved maintainability and uptime
- scalable architecture patterns
- reduced technical content review time by nearly 90%
- close stakeholder collaboration
- translated user workflows into intuitive software
- highly receptive to feedback
- improved retrieval accuracy and response quality
- improved customer experience
- strong initiative
- performed well in ambiguous zero-to-one environments
- effective prioritization under limited oversight
- independently drove execution with minimal oversight
Aniruddha's references speak for themselves. Let us connect you.
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