• Engineered GenAI-powered applications using Python, LangChain, RAG pipelines, and Agentic AI to deliver real-time, context-aware assistance within Target’s Store Companion platform, supporting 400,000+ users.

• Built scalable backend microservices and vector retrieval systems leveraging PostgreSQL, Kafka, and embedding stores, enabling fast semantic search, long-term memory, tool calling, and LLM-driven reasoning workflows.

• Developed and optimized API/function services in Kotlin to orchestrate LLM calls, manage embeddings, and support autonomous, agent-like task execution using planning, tool routing, and contextual grounding.

• Contributed to frontend development using React & TypeScript to surface LLM-generated insights and interactive workflows, ensuring seamless full-stack integration between AI systems and UI components.

• Developed machine learning pipelines for prompt chaining, model evaluation, feature logging, embedding generation, and vector indexing, collaborating with data and platform teams to ensure scalable, high-quality model integration into production systems.

• Implemented production-grade observability—metrics, logging, dashboards—to ensure system reliability, safety, and performance at scale.

• Designed and implemented RESTful APIs and backend services in Java and Kotlin, supporting scalable data flows and high-availability server-side functionality for applications.

• Engineering and optimized MongoDB and PostgreSQL/SQL databases , implemented high-performance queries, and built resilient server-side logic to support scalable, low-latency backend services.

• Developed automated CI/CD pipelines to compile builds, execute unit/integration tests, enforce code quality, and streamline production deployments.

• Implemented Agile/Scrum workflows and participated in architectural design discussions, helping define API contracts, service boundaries, and data models while delivering robust backend features through iterative development and code reviews.

• Automated infrastructure provisioning and configuration using Ansible, improving deployment consistency, reducing manual setup, and enabling repeatable Infrastructure-as-Code workflows across internal platforms.

• Built Python automation tools for data processing, operational workflows, and internal dashboards, reducing manual intervention and improving system visibility for DevOps engineering teams.

• Wrote Linux shell scripts for server administration, log processing, monitoring tasks, and recurring maintenance, leading to greater system stability and lower operational overhead.

• Created a framework of actionable touchscreen interaction design recommendations for children as part of the TIDRC project.

• Evaluated the types of design recommendations that developers implement in kids’ apps.

• Worked on updating and expanding the current recommendation framework by gathering new data published by Human-Computer Interaction researchers.

• Solved customer software issues by debugging, troubleshooting, and offering advice to customers.

• Recorded technical reports and documented cases on Salesforce platform.

• Efficiently handled multiple customer issues per day and closed 100% of support tickets.