• Code review for PRs and having the final approval for merging the code.
• Along with the Dev Lead/Scrum Master, help resolve technical impediments that the team
are facing that may not be related to the story they are developing e.g. environment issues,
pipeline issues, 3rd party issues etc
• Triage point(“the bouncer”) for high priority production issues following release to prod
• Review the ‘feature’ level requirements (functional and non-functional) and acceptance criteria and validate they align with the current platform capabilities, KDDs, patterns. If there is a mismatch raise this back to tech governance team.
• Work directly with the Boots SA
• Articulate where there are areas of complexity and risk
• Articulate options on key design decisions within the commerce component and support the Boots SA to conclude the decision
• Ensure non-functional/operational requirements have been taken into consideration in the design process (performance, security, deployment approach etc)
• Review UX design and identify any areas which may need more clarity or are open for interpretation or deviate from patterns and work with the UX team and PO to resolve.
• Work with PO to structure the user stories in a way that is best consumed by dev team, in conjunction with discussion with the dev lead
• call out when ‘earlier’ technical complexity, assumptions, dependencies are changing during refinement especially if business value is not changing alongside
• Along with the scrum master, help resolve any technical blockers faced by the team especially in relation to dependencies/services of teams outside the scrum team
• Provide input to deployment team about the specific deployment requirements/dependencies. Review and sign off the deployment plan.

Interface to
• teams/demands outside the scrum team Solution Architects, UX team, Test team, service team, third party tech leads, DevOps team.

ADA AI – Enterprise AI Platform with Microservices & Conversational Database Queries

I contributed to the development of ADA AI, an enterprise AI-driven platform built with a microservices architecture and modern frontend applications, enabling users to interact with databases using natural language queries.

Frontend (FE)
Two Angular 17 applications: one for administrators and one for clients
UI built with Kendo UI for complex grids, charts, and dynamic forms
Users can “talk” to the database in human language → system translates queries into SQL via AI models

Backend (BE)
3 Node.js microservices:
Orchestration MX – Express.js-based orchestrator handling API Gateway and communication between services
AI MX – MCP-based architecture for generating AI-powered database queries (NLP → SQL translation)
DB MX – Express.js microservice connecting to multiple database types (Oracle, PostgreSQL, Firebird, MariaDB).
Retrieves DB schema, tables, and metadata
Executes select queries generated by AI
Includes unit testing and integration testing for query validation

Infrastructure: Kubernetes for container orchestration and scalability

My Role:

• Designed and prepared the overall project architecture (FE + BE + microservices + orchestration)
• Implemented the two Angular 17 applications (admin & client) with Kendo UI
• Developed the DB MX microservice, ensuring reliable multi-database support and query execution
• Coordinated team efforts to deliver the AI MX and Orchestration MX services
• Improved team workflows by adopting the latest development tools and procedures (CI/CD, code reviews, testing standards)
• Ensured smooth collaboration across frontend, backend, and AI engineers within an agile setup

This project gave me the opportunity to work hands-on with microservices, AI-powered query generation, Kubernetes deployment, and enterprise-level Angular applications while also leading architectural design and cross-team coordination.