Python Backend Engineer Cloud GenAI Specialist

JaswanthRaj Bantu Aindla

Python Developer Backend Engineer Cloud & GenAI Specialist

Charlotte, NC

Email: *****************@*****.*** Phone: 475-***-****

LinkedIn: https://www.linkedin.com/in/jaswant-raj-bantu-aindla-380876228

Professional Summary:

Backend Python Developer with 5+ years of experience designing, developing, and deploying scalable backend systems, cloud-native microservices, and AI/GenAI-powered automation for banking, insurance, and financial domains. Skilled in Python (Django, Flask, FastAPI), REST/GraphQL APIs, serverless and event-driven architectures, and cloud platforms (AWS, GCP, Azure). Proficient in containerization (Docker, Kubernetes, Helm), CI/CD automation (Jenkins, GitLab, Terraform), and data engineering pipelines (PySpark, Airflow, Delta Lake, ETL). Experienced in designing AI/GenAI solutions, integrating LLMs for fraud detection, analytics, and workflow automation. Adept at Agile/Scrum practices, mentoring teams, and leading cloud migration and microservices transformation projects. Strong focus on high availability, observability, performance optimization, and security compliance.

Technical Skills:

Programming Languages: Python, Java, JavaScript, TypeScript, SQL, Shell Scripting

Frameworks & Libraries: Django, Flask, FastAPI, Node.js (Express), Spring Boot, Pandas, NumPy, PySpark, TensorFlow, PyTorch

Cloud Platforms & DevOps: AWS (Lambda, EKS, ECS, EC2, S3, RDS, DynamoDB, API Gateway, CloudFormation), Azure, GCP

Containerization & Orchestration: Docker, Kubernetes, Helm Charts, ECS/Fargate

CI/CD & Automation: Jenkins, GitLab CI/CD, Terraform, Ansible, CircleCI, GitOps

Databases & Data Engineering: SQL, Oracle, PostgreSQL, MySQL, MongoDB, Cassandra, Redis, ETL pipelines, Delta Lake, Data Modeling, Data Lakes

Messaging & Streaming: Kafka (Streams & Topics), RabbitMQ, AWS SQS/SNS, Event-driven Microservices

API & Security: RESTful APIs, GraphQL, OAuth2, JWT, API Security Best Practices

GenAI & AI Integration: Large Language Models (LLMs), GPT APIs, AI-powered dashboards, Intelligent Automation, ML pipeline integration

Testing & Quality: Unit Testing, Integration Testing, End-to-End Testing, PyTest, Selenium, Cypress, Jest, JUnit, TDD

Monitoring & Observability: Prometheus, Grafana, CloudWatch, ELK Stack, Application Performance Monitoring (APM)

Frontend & Analytics: React.js, Angular, Vue.js, Dash/Plotly, Looker, Tableau, Power BI

Collaboration & Agile Tools: Jira, Confluence, Git, Mentorship, Code Reviews, Agile/Scrum

Professional Experience:

GenAI Python Developer Bank of America, Charlotte, NC Mar 2025 – Present

Environment: Python, Django, Flask, FastAPI, SQL, MySQL, Oracle, Spring Boot, React.js, Angular, AWS (Lambda, EKS, ECS, S3, RDS, DynamoDB, API Gateway, CloudFormation), Docker, Kubernetes, Helm, Jenkins, GitLab, Looker, Prometheus, Grafana, ELK Stack, PostgreSQL, MongoDB, Redis, LLM APIs (GenAI)

Designed and implemented event-driven microservices for financial workflows using Django, FastAPI, and Spring Boot.

Developed REST and GraphQL APIs secured with OAuth2/JWT for multi-system integration.

Integrated GenAI (LLMs) to automate fraud detection, predictive analytics, and real-time insights dashboards.

Experience with Big Data platforms/tools (Linux, HDFS, Hive, Hortonworks, Spark, Scala, Python, Java, Kafka

Implemented scalable API-based data ingestion pipelines supporting millions of daily transactions.

Designed and optimized SQL queries for AWS RDS databases to support analytical workloads and reporting systems.

Enhanced SQL and Python query performance, reducing execution time by 30% and improving data retrieval efficiency.

Leveraged MongoDB (NoSQL) to store and inquiry datasets exceeding 6,000 records, minimizing data retrieval times by 30 seconds per query and enhancing reporting efficiency for real-time news analytics.

Built RESTful APIs using Python to enable secure data exchange between data platforms and business applications.

Automated reporting, workflow orchestration, and serverless functions using AWS Lambda, S3, and RDS.

Worked with Data Engineering team to Automate ETL workflows using Python scripts and Spark jobs running on Hadoop clusters.

Monitored data pipelines and optimized Spark performance by tuning partitioning, caching, and memory configurations.

Developed scripts in Linux environments for scheduling batch jobs and data ingestion tasks.

Data processing experience (Join, Merge, Transform, Summarize)

Migrated legacy monolithic applications to AWS EKS/ECS microservices for scalability and reliability.

Containerized microservices with Docker and orchestrated deployments with Kubernetes and Helm Charts.

Built AI-powered analytics dashboards using React.js/Angular and Looker for fraud, risk, and transaction monitoring.

Configured monitoring, logging, and alerting with Prometheus, Grafana, CloudWatch, and ELK Stack.

Established CI/CD pipelines with Jenkins, GitLab CI/CD, and Terraform for zero-downtime deployments.

Reduced API response times by 30% through query optimization and caching strategies.

Led migration of monolithic applications to AWS microservices architecture.

Built event-driven data pipelines processing millions of financial transactions daily.

Automated fraud analytics workflows using LLM-powered solutions.

Collaborated with data analysts and business teams to translate data requirements into scalable data engineering solutions.

Conducted code reviews, and ensured coding standards in Agile/Scrum teams.

Full Stack Developer Blue Cross Blue Shield (BCBS), India (Offshore) Aug 2021 – Apr 2023

Environment: Python, Flask, Django REST Framework, SQL, ORACLE, MongoBD, Vue.js, Vuex, Vuetify, AWS (Lambda, SQS, SNS, ECS, EKS), Kafka, Terraform, CloudFormation, PostgreSQL, MongoDB, Docker, Kubernetes, CircleCI, PyTest, Cypress

Developed scalable backends and APIs for policy and claim management systems.

Built responsive SPAs using Vue.js, Vuex, and Vuetify for real-time user portals.

Implemented serverless workflows with AWS Lambda, SQS, and SNS to streamline asynchronous processing.

Developed customer segmentation models using Python and SQL to identify high-value traveler cohorts for targeted marketing.

Developed and optimized complex SQL queries involving multi-table joins, subqueries, window functions, and aggregations to process large datasets efficiently.

Deployed containerized applications on AWS ECS/EKS with auto-scaling and high availability.

Integrated Kafka-based event-driven architecture for messaging, audit logging, and real-time claim processing.

Developed data validation and control checks to identify missing, duplicate, and inconsistent records in data pipelines.

Integrated Kafka streaming data pipelines for real-time ingestion and processing of financial transaction data.

Created data quality checks and validation frameworks to ensure integrity across multiple data sources.

Integrated datasets into AWS RDS relational databases for downstream reporting applications.

Developed reusable Python libraries for data transformation and validation.

Managed infrastructure as code using Terraform and CloudFormation for consistent environment provisioning.

Optimized databases and queries in PostgreSQL and MongoDB for faster retrieval and reliability.

Conducted unit, integration, and end-to-end testing using PyTest and Cypress.

Built analytics dashboards and reports using Looker and Tableau to support management decisions.

Python Developer Jade Global, Inc., Hyderabad, India Jul 2019 – Jul 2021

Environment: Python, Django, PostgreSQL, SQL, Oracle, Celery, PySpark, Apache Airflow, Kafka, MongoDB, Cassandra, Docker, Kubernetes, Jenkins, Dash, React.js, Pandas, NumPy

Led development of trade reconciliation platform using Django, PostgreSQL, and Celery.

Built ETL pipelines with PySpark, Airflow, and Kafka for financial data ingestion and processing.

Migrated legacy SQL systems to MongoDB and Cassandra to improve performance and enable real-time analytics.

Automated compliance reporting using Pandas and NumPy.

Developed real-time dashboards using Dash and React.js for portfolio analytics.

Implemented RESTful APIs for integration with external trading and risk systems.

Containerized Python microservices with Docker and orchestrated deployments using Kubernetes.

Configured CI/CD pipelines with Jenkins for automated testing and deployments.

Collaborated with teams on cloud migration, performance tuning, and microservices adoption.

Education

Master of Science in Computer Science

University of Bridgeport, Connecticut Dec 2024

Bachelor of Technology, Computer Science

JNTUH University Aug 2015-May 2019

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