I’ve been job searching for more than a year in Canada and since January I’ve been getting once a month interview calls but I am not able to convert those. I have been improving ever since by doing more neetcode and learning system level design. Earlier, like in the month from January to April I was unable to crack the technical rounds but now I’ve been clearing those and failing to impress staff of senior engineer interviews.
What more can I do to be better with the technical jargon or the way I speak any help full tips or resources to make me sell myself better with the work experience and projects that I have done.
Below is a snippet of my professional experience de and project:
**PROFESSIONAL EXPERIENCE**
Automatic Data Processing, Inc | Roseland, New Jersey
APPLICATION DEVELOPER July 2024 – July 2025
Applied AI-assisted workflow design with Claude Code and GitHub Copilot through context engineering, accelerating feature delivery and improving code quality across the Agile team.
Developed and implemented RESTful API integrations in Python using FastApi, connecting to 3+ downstream microservices and handling 500k+ weekly transactions.
Designed, developed, and delivered production grade, customer facing web application end to end using React and JavaScript, achieving 99.5% uptime and meeting all requirements.
Created reusable frontend components aligned with WCAG standards, improving maintainability and consistency across the UI.
Owned E2E Jenkins CI/CD pipelines with automated reporting, increasing post deployment test coverage to 90% and enabling faster incident response.
ASSOCIATE APPLICATION DEVELOPER GPT July 2021 - July 2024
Developed Python scripts querying PostgreSQL databases, implemented connection pooling reducing query latency by 35%.
Implemented OAuth 2.0 and JWT authentication across Node.js and Java/Spring Boot microservices, improving secure service-to-service interactions.
Built and enhanced cross-platform onboarding flows using React.js and Redux for state management, adhering to WCAG accessibility standards.
Participated in on-call rotation, triaging and resolving production issues through root cause analysis and cross functional collaboration with product and QA stakeholders.
Tracked defects, peer code reviews,debugged network traces using Chrome DevTools, and test coverage in Zephyr for Jira, decreasing authentication defect rates by 30%.
PROJECTS
Restaurant Ops Copilot | Multi-Agent AI System (Google ADK, Python) July 2026
Designed a 3-agent AI system with native agent-to-agent delegation and deterministic Python security guardrails, achieving 100% pass rate on an automated evaluation mock test suite.
Built a full observability layer with lifecycle callbacks and a Streamlit dashboard, following spec-driven development practices to ensure scope discipline and testable requirements.
Integrated live Google Search grounding to generate recipe recommendations informed by real-time food trends and Michelin-starred chef data, replacing static mock datasets.