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Manasa Pantra
Junior Software Engineer specializing in AI, LLM systems, and full-stack development
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About
Product-focused full-stack engineer at startup (Zippy) who shipped a production multi-agent AI system for restaurant operations plus payments workflows. Built end-to-end: RAG grounded on a Notion knowledge base, structured function-calling task routing, FastAPI/JWT multi-tenant backend, and a polished React+TypeScript owner dashboard. Has real production incident experience (duplicate Stripe webhooks) and reports ~94% task-routing accuracy under load.
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Key Strengths
- Shipped multi-agent AI system to production for restaurant operations
- Improved production AI reliability via RAG grounding + clarification flows to reduce hallucinations
- Designed robust task routing using structured function calling with strict schemas (valid JSON before actions)
- Built customer-facing AI menu management with validation + confirmation layers for high-impact changes
- Owned FastAPI backend with JWT auth, multi-tenant authorization, versioned APIs, and standardized errors
- Production reliability engineering: idempotent Stripe webhooks, retries, async non-blocking external calls
- Performance/scale practices: caching, horizontal scaling behind load balancer, monitoring latency/error rates
- React+TypeScript dashboard with typed hooks, consistent loading/error UX, optimistic updates with rollback
- PostgreSQL modeling for conversations/intents/knowledge-graph entities with indexing and query-driven tuning
- Handled real production incident: duplicate Stripe webhook events under high traffic; fixed via event-id checks and faster webhook responses
- Reported ~94% accurate task routing under production load and continuously monitored/improved it
- Built and deployed an LLM assistant that can take real operational actions (not just chat)
- Strong focus on production reliability; implemented retrieval-only answering to reduce hallucinations
- Designed guardrails and verification steps before making business-critical updates
- Effective multi-agent orchestration for decomposing complex requests into parallel tasks with all-or-nothing updates
- Practical testing strategy covering edge/failure scenarios plus agent-level isolation testing
- Metrics- and logging-driven evaluation in production (accuracy, success rate, response time; decision traceability)
- Pragmatic model/retrieval/prompt selection based on accuracy/speed/cost/reliability tradeoffs
- Able to translate non-technical stakeholder needs into usable product features via demos and iterative feedback
Reference Highlights
- Strong at understanding requirements
- Consistently delivers production-ready, customer-facing features
- Significant impact on team despite joining later
- Built internal tools used by the entire team
- Reliable and consistent; never missed a deadline
- Proactive progress communication
- Improved operational efficiency via active-orders monitoring tool
- Helped ensure strong customer experience by catching order/delivery issues quickly
- Strong end-to-end full-stack execution
- Writes good modular code
- Rigorous testing; code is dependable
- Exceptional React/TypeScript frontend results
- Professional, intuitive design/UX skills
- Takes feedback well and iterates effectively
- Strong PostgreSQL/SQL and relational modeling
- Takes initiative in AWS deployment/operations
- Performs well during production issues/incidents
- Drives ideas from 0 to 1 in ambiguous environments
- Collaborates closely with founders/leadership with minimal oversight
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