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Full-stack software engineer with 4+ years delivering production MCP-based agentic integrations, RAG pipelines, and LLM-powered automation for real-time enterprise intelligence. Experienced in cloud-native microservices, event-driven architectures, and end-to-end ownership from design and APIs through CI/CD and observability at enterprise scale. Builds scalable systems on AWS and GCP, modernizing legacy services and delivering greenfield platforms that improve operational efficiency—leveraging semantic search, vector embeddings, intent-based orchestration, and AI retrieval optimization to reduce resolution time and improve contextual relevance.…Full-stack software engineer with 4+ years delivering production MCP-based agentic integrations, RAG pipelines, and LLM-powered automation for real-time enterprise intelligence. Experienced in cloud-native microservices, event-driven architectures, and end-to-end ownership from design and APIs through CI/CD and observability at enterprise scale. Builds scalable systems on AWS and GCP, modernizing legacy services and delivering greenfield platforms that improve operational efficiency—leveraging semantic search, vector embeddings, intent-based orchestration, and AI retrieval optimization to reduce resolution time and improve contextual relevance.

NIKSHITHA AELLA

Full Stack Developer, Back-End Developer, AI Developer, +2

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Full-stack software engineer with 4+ years delivering production MCP-based agentic integrations, RAG pipelines, and LLM-powered automation for real-time enterprise intelligence. Experienced in cloud-native microservices, event-driven architectures, and end-to-end ownership from design and APIs through CI/CD and observability at enterprise scale. Builds scalable systems on AWS and GCP, modernizing legacy services and delivering greenfield platforms that improve operational efficiency—leveraging semantic search, vector embeddings, intent-based orchestration, and AI retrieval optimization to reduce resolution time and improve contextual relevance.…Full-stack software engineer with 4+ years delivering production MCP-based agentic integrations, RAG pipelines, and LLM-powered automation for real-time enterprise intelligence. Experienced in cloud-native microservices, event-driven architectures, and end-to-end ownership from design and APIs through CI/CD and observability at enterprise scale. Builds scalable systems on AWS and GCP, modernizing legacy services and delivering greenfield platforms that improve operational efficiency—leveraging semantic search, vector embeddings, intent-based orchestration, and AI retrieval optimization to reduce resolution time and improve contextual relevance.

Available to hire

Full-stack software engineer with 4+ years delivering production MCP-based agentic integrations, RAG pipelines, and LLM-powered automation for real-time enterprise intelligence. Experienced in cloud-native microservices, event-driven architectures, and end-to-end ownership from design and APIs through CI/CD and observability at enterprise scale.

Builds scalable systems on AWS and GCP, modernizing legacy services and delivering greenfield platforms that improve operational efficiency—leveraging semantic search, vector embeddings, intent-based orchestration, and AI retrieval optimization to reduce resolution time and improve contextual relevance.

Skills

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Work Experience

Software Engineer, AI Platforms at Lowe’s Companies, Inc., USA

July 1, 2025 - Present

Built an enterprise AI support platform using Python, FastAPI, LangChain, and LLMs to resolve contextual support queries via RAG across documentation, PostgreSQL, and Elasticsearch—reducing ticket resolution time by 55% and eliminating manual escalation for 100+ engineers. Developed scalable document ingestion and embedding pipelines indexing 10K+ technical support documents into Pinecone, enabling semantic search with sub-second retrieval. Applied semantic chunking, metadata filtering, and retrieval optimization to improve similarity precision by 35%, reduce hallucination rate by 28%, and improve contextual relevance. Implemented custom MCP servers exposing live REST APIs for PostgreSQL and Elasticsearch to let LLM agents query structured operational data and retrieve real-time logs, cutting troubleshooting lookup time by 65%. Created intent-based workflow orchestration to route queries across RAG and MCP services, automating resolution for 60% of recurring ticket categories. Used L

Software Engineer at UnitedHealth Group (UNC Charlotte Research Collaboration)

January 1, 2024 - May 31, 2025

Built HIPAA-compliant Prior Authorization REST APIs using Java 17, Spring Boot, and Cassandra. Implemented rule-based workflows that automated 65% of routine authorization decisions and reduced processing time from 2+ business days to under 4 hours. Integrated RabbitMQ for asynchronous event-driven communication between auto-approval and other platform services and implemented Redis caching to reduce database calls by 40%, lowering response latency by 35% under peak load. Developed provider-facing React UI modules with SSO authentication, validation, and real-time status rendering for 50+ healthcare providers, reducing support escalations by 45%. Deployed on Kubernetes with Prometheus monitoring, and set up CI/CD pipelines (GitHub Actions, Jenkins) to reduce MTTD for incidents by 50% during research trials.

Software Engineer at Verizon, India

October 1, 2022 - September 30, 2023

Developed a contract document generation platform (Java, Spring Boot, Angular, Node.js) replacing manual signing workflows and scaling to 50K+ customers monthly, reducing document processing time from 3+ days to under 2 hours. Refactored a tightly coupled monolith into three deployable microservices using REST APIs and Spring, enforcing OpenAPI specs and Swagger validation, enabling independent release cycles and reducing deployment failures by 60%. Built an event-driven messaging layer (JMS, RabbitMQ) decoupling provisioning, billing, and contract services, cutting end-to-end latency from 5+ minutes to under 30 seconds. Configured AWS infrastructure (EC2, Auto Scaling, load balancing, CloudWatch) and implemented CI/CD pipelines (Jenkins, GitLab), adding JWT/OAuth 2.0 security controls to reduce average deployment cycle time by 40% and enable zero-downtime releases. Established end-to-end test coverage (JUnit, Cucumber, Cypress) across AWS EKS deployment pipelines, achieving 85%+ cover