Bhanvi Menghani
@bhanvimenghani
I build production-ready APIs and AI-powered features, blending backend engineering, ML, and UI delivery.
What I'm looking for
As an IBM Software Developer 2, I design and implement production-ready REST APIs for the Layers module, delivering structured visibility into application stack configurations and their dependencies while improving performance and reliability.
I lead end-to-end delivery of AI & LLM engineering work, including a customer-requested enterprise feature using Model Context Protocol (MCP), Retrieval-Augmented Generation (RAG), and prompt/context engineering to tailor recommendation cycles to real operational behavior.
I continuously upgrade systems by refactoring 10+ legacy components to align with standardized engineering practices, reducing technical debt and strengthening long-term maintainability. I also build and validate solutions with PyTest, Cypress, and Kubernetes-native tooling.
My work spans backend, frontend, and cloud-native delivery—whether architecting an MVP for AI Agents using the LLAMA stack and MCP servers or developing GPU workload benchmarking workflows and Prometheus-based metrics. I’m also motivated by impact, backed by top hackathon outcomes and active open-source contributions.
Experience
Work history, roles, and key accomplishments
Designed and implemented 5 production-ready APIs for the Layers module, improving structured visibility into application configuration dependencies for more reliable performance tuning. Led an enterprise feature for AI/LLM clients using Model Context Protocol (MCP) and refactored 10+ legacy components to align with standardized engineering practices and improve maintainability.
Built Kruize configuration management capabilities by designing and integrating RESTful APIs for recommendation enablement while reducing data storage and processing overhead. Automated Prometheus-based resource usage metric collection and benchmarking workflows, reducing manual effort by 80%.
Designed and integrated RESTful APIs for managing Kruize configuration parameters to enable precise recommendation cycles while reducing data storage and processing overhead. Delivered and deployed the Kruize UI for a Kubernetes resource optimization platform, independently managing requirements across stakeholders to improve onboarding and usability.
Contributed to test automation, frontend development, and UI/backend design tasks, ramping up quickly and delivering full-stack work. Supported end-to-end development across multiple components during the internship period.
Education
Degrees, certifications, and relevant coursework
Jaipur Engineering College and Research Centre
B.Tech, Information Technology
2018 -
Grade: CGPA: 9.67/10
Earned a B.Tech in Information Technology, maintaining a CGPA of 9.67/10 across 8 semesters.
Tech stack
Software and tools used professionally
Availability
Location
Authorized to work in
Job categories
Skills
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