Full Stack Developer (AI/ML) 4+ Years Experience

Kushal Shah

Full Stack Developer (AI/ML)

******@************.*** 817-***-**** USA LinkedIn GitHub Summary

Full Stack Software Engineer with 4+ years of experience building scalable backend systems, data-driven applications, and modern web platforms. Strong focus on AI/ML-powered backend services, data engineering, and analytics, with hands-on experience in Python-based frameworks, cloud-native architectures, and data visualization. Proven ability to design APIs, optimize databases, integrate ML models into production systems, and collaborate cross-functionally in Agile environments. Actively aligned with current market demand in AI, Data Engineering, and Full Stack development.

TECHNICAL SKILLS

Languages: Python, TypeScript, JavaScript, R

AI / ML: scikit-learn, PyTorch, TensorFlow, LangChain, OpenAI APIs, Hugging Face Backend & APIs: FastAPI, Flask, REST APIs, GraphQL, Microservices Data & Big Data: Apache Spark, Databricks, ETL Pipelines Databases: PostgreSQL, MongoDB, Redis, pgVector

Frontend: React.js, Next.js, HTML, JavaScript, Tailwind CSS, D3.js, Chart.js, Power BI Cloud & DevOps: AWS (ECS, RDS, CloudWatch), Docker, CI/CD (GitHub Actions) Tools: Git, Agile/ScrumProfessional Experience

Professional Experience

Full Stack Developer (AI / Data), State Street Corporation 05/2024 – Present Remote, USA

• Modernized a large-scale Policy Management platform into a data-driven, cloud-native application, improving operational efficiency by 40%.

• Designed and developed backend services in Python (FastAPI, Flask) to support analytics, reporting, and AI-enabled decision workflows.

• Integrated machine learning models (Random Forest, predictive scoring) into backend pipelines to enhance risk assessment and underwriting accuracy.

• Implemented data ingestion and processing pipelines, enabling near real-time analytics using structured and semi-structured data sources.

• Optimized PostgreSQL schemas and queries, reducing API response times by 30% and improving reliability under high load.

• Built secure and scalable REST APIs, supporting audit logging, policy versioning, and role-based access controls.

• Leveraged Redis for caching and performance optimization in high-traffic workflows.

• Deployed and monitored services on AWS ECS, implementing CI/CD pipelines with blue-green deployments and achieving 99.95% uptime.

• Collaborated with data analysts, product owners, and UX teams in Agile sprints to deliver production-ready AI-enable d features. Full Stack Developer (Data / Backend), Tatvasoft 06/2019 – 12/2022 Gujarat, India

• Developed backend APIs and data services supporting analytics-heavy insurance and public safety platforms.

• Built data processing and reporting modules to support business intelligence and operational dashboards.

• Implemented Redis-based caching and optimized database access patterns, improving system performance by 20%.

• Designed secure authentication and authorization workflows for distributed services.

• Created interactive frontend dashboards using React.js, enabling stakeholders to visualize KPIs and operational metrics.

• Participated in end-to-end SDLC activities including requirement analysis, system design, testing, and production support.

• Contributed to Agile ceremonies, sprint planning, and continuous improvement initiatives. Education

Bachelor of Engineering in Computer Engineering Gujarat Technological University, Gujarat, India 08/2016 – 08/2020 Master of Science in Computer Science University of Texas at Arlington, Texas, USA 01/2023 – 12/2024 Projects

Skill Bridge (Python, React.js, TypeScript)

• Improved real-time test data visualization accuracy by 18% by building backend analytics modules in Python and integrating predictive models (scikit-learn), with results stored and queried using PostgreSQL.

• Leveraged AI/ML tools to automate data labeling and performance monitoring, increasing efficiency by 20%. Gemstone Guard (React.js, TypeScript, Java, PostgreSQL, Python, scikit-learn)

• Increased dashboard responsiveness by 22% by developing backend services in Java (Spring Boot) and optimizing SQL queries in PostgreSQL, while integrating machine learning modules.

• Collaborated with cross-functional teams to troubleshoot and resolve technical issues, ensuring high system uptime.

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