10 years of experience in developing, engineering, testing, designing and implementing

of various standalone and client-server architecture-based application software in Python,

Rust, Go and Javascript. There is also a lot of experience in blockchain and machine learning, computer vision.

AND THERE IS MY EXP:

Languages: Python, Go, Rust, Javascript, Typescript

Frameworks: Django(DRF, DC), Flask, FastAPI, ReactJS, Angular, ReactJS, VueJS, NodeJS, Tensorflow, PyTorch, Pyramid, CherryPy

Cloud Environment: AWS(EC2, S3, RDS, Elastic Beanstalk, Cognito,

IAM, Sagemaker, Glacier, ECR, ECS, Batch, Step Functions, Lambda,

CloudWatch, CloudFront, ElastiCache), GCP, Azure, DO

Operating System: Linux, Windows, MacOS

Tools: Celery, RabbitMQ, SQLAlchemy, Redis, Docker, Kubernetes,

Elasticsearch, Keras, Jira, OpenCV, Numpy, Skimage, Matplotlib, Scipy,

Pandas, OpenNN, Google ML Kit, Apache Spark, SpaCy, GraphQL

Databases: PostgreSQL, MongoDB, MySQL, Aurora, DynamoDB, Cassandra

Servers: Nginx, Apache

Web3.0: Solidity, Solana, web3, Hardhat, Metaplex

• Cost Savings – Saved over $120,000/year by aggressively optimizing Airflow DAGs, BigQuery costs, and GCP compute workloads.

• Speed Improvements – Reduced execution time by 80% by rewriting bloated Python ETL jobs into async, caching-heavy microservices.

• AI Moderation – Built self-learning AI moderation engine with CNN+RNN hybrid models to detect offensive content across platforms.

• Security – Uncovered critical security holes in data ingestion layer—patched before they reached production.

• Scalability – Scaled event processing from 50K/day to 10M+/day, implementing autoscaling queues and zero-downtime deploys.

• Genomics – Designed serverless genome analysis system for biomedical data using Lambda, Batch, S3, and 50-step Step Functions.

• DevOps – Migrated monolith to microservices and reduced CI/CD deploy time from 60 mins to 4.5 mins.

• Leadership – Led high-stakes client negotiations with C-levels on ML infrastructure, compliance, and performance SLAs.

• Airflow Optimization – Refactored legacy Airflow DAGs with dynamic mapping & XCom suppression — halved orchestration overhead.

• API Modernization – Rewrote fragile Flask API into robust FastAPI backend with typed endpoints and 5× faster response time.

• Team Building – Hired, mentored, and scaled elite teams of Python, ML, and DevOps engineers across 4 countries.

• Computer Vision – Designed real-time image classification flow using TensorFlow Lite + OpenCV, used in moderation pipelines.

• Financial ETL – Reduced financial data reconciliation latency by 94%, implementing parallelized async pipelines across 3 cloud regions with transactional guarantees.

• LLM Integration – Integrated LLM-powered assistants into internal tools — accelerated analyst workflows by 6× and reduced support tickets by 70%.

• FinTech ML – Led cross-border rollout of a risk scoring engine for financial institutions, blending real-time Kafka streams and explainable ML models.

• Product Thinking – Collaborated directly with VC-backed C-suite execs, translating vague business ideas into scalable, cloud-native architectures with zero vendor lock-in.

• Model Maintenance – Developed AI feedback loop retraining system for production models based on user signals & drift detection.

• Automation – Reverse-engineered undocumented APIs and built full automation wrappers around them in under a week.

• Internal Tools – Created internal service marketplace — sold 6+ tools to partner teams, increasing org-wide reusability.