.png){kind=logo}
Dhanush Kukatla
Mid Software Engineer specializing in backend distributed systems and AI/RAG platforms
Connect with Dhanush
Dhanush already has a relationship with Reval, so a warm intro from us gets a much better response than cold outreach.
Recommended
Already have an account?
About
Full-stack engineer with hands-on ownership of a production AI knowledge assistant used by 10,000+ daily users. Combines React/Next.js frontend work with FastAPI, AWS serverless, and RAG architecture using GPT-4, LangChain, and Pinecone, with measurable impact on relevance, latency, uptime, and support deflection.
Find your next great hire
Our AI agents source, screen, and vet candidates for your open roles. Get qualified candidates within 48 hours.
Key Strengths
- Owned end-to-end full-stack delivery of an AI knowledge assistant in production
- Built and shipped RAG-based AI systems using GPT-4, LangChain, and Pinecone
- Strong React/Next.js and FastAPI full-stack architecture experience
- Production-scale cloud deployment on AWS with serverless infrastructure and CI/CD
- Performance optimization for AI systems with caching and retrieval tuning
- Reliability-focused engineering with monitoring, testing, and feature-flag rollouts
- Data-driven product improvement using analytics, user feedback, and production metrics
- Scaled product to 10,000+ daily users with 99.99% uptime
- Improved answer relevance by 30%
- Reduced user query response time by 45%
- Reduced manual support requests by about 70%
- Zero-to-one product ownership in ambiguous stakeholder environments
- Strong stakeholder alignment and roadmap prioritization across business teams
- Designed intuitive AI experiences for non-technical users with source transparency
- Shipped production LLM knowledge assistant used by 10,000+ daily users
- Reduced average support resolution time from 18 minutes to 12 minutes
- Improved retrieval precision ~20% via sliding-window chunking + semantic deduplication
- End-to-end RAG productionization (ingestion, embeddings, vector store, streaming responses with citations)
- Designs robust failure-mode handling (rate limits, transient errors, retries/timeouts, fallbacks)
- Architects multi-step agent workflows with tool calling, structured outputs, and stateful orchestration
- Builds evaluation + monitoring loops (offline relevance benchmarks + online KPIs) reducing MTTD to <15 minutes
- Strong data-quality/ERP integration practices (validation, normalization, RBAC, idempotency, safe retries)
Like what you see? We'll introduce you to Dhanush directly.
Experience
Education
Skills
Languages
Certifications
Browse Similar
Similar Candidates
Senior Full-Stack Software Engineer specializing in cloud-native distributed systems and AI
Vinh Ly
Staff Software Engineer specializing in scalable full-stack FinTech systems
“Full-stack/backend engineer with recent hands-on experience building an AI-powered AML/KYC platform for financial institutions, spanning Go/Python backend services, real-time risk pipelines, and React/TypeScript analyst dashboards. Stands out for measurable compliance-tech impact: 94% fewer false positives, review times reduced from days to hours, and microservices processing 10,000+ transactions per second.”
Senior AI/ML Engineer specializing in applied AI and scalable backend systems
Staff Software Engineer specializing in distributed infrastructure and reliability
Staff-level Software Engineer specializing in LLM inference infrastructure and scalable model serving
Senior Full-Stack Engineer specializing in AI/ML platforms and cloud-native systems
Interested in Dhanush?
We'll personally introduce you - no strings attached.
Build your dream team with Reval
Our AI agents source, screen, and vet candidates for your open roles. Get qualified, high-intent candidates on your desk within 48 hours.
Discover more candidates like Dhanush
Search across thousands of pre-screened, high-quality, high-intent candidates on Reval.
Search Talent