Lovejinder Singh

Skills

Python, Core Python, Advanced Python, Object-Oriented Programming (OOP), Functional Programming, Multithreading, Multiprocessing, AsyncIO, Data Structures, Algorithms, Design Patterns, SOLID Principles, Software Engineering, REST APIs, GraphQL, FastAPI, Flask, Django, Django REST Framework (DRF), SQLAlchemy, Pydantic, Celery, Gunicorn, Uvicorn, Microservices, Serverless Architecture, Event-Driven Architecture, API Gateway, WebSockets, gRPC, OpenAPI, Swagger, Postman, JSON, XML, YAML, OAuth 2.0, JWT, OpenID Connect (OIDC), SAML, RBAC, Authentication, Authorization, Rate Limiting, API Security, Python Scripting, Bash, PowerShell.

NumPy, Pandas, SciPy, Polars, Dask, PyArrow, Apache Spark, PySpark, Hadoop, Hive, Databricks, Delta Lake, Delta Tables, Unity Catalog, Databricks Asset Bundles (DAB), Apache Airflow, Prefect, Luigi, ETL, ELT, Data Pipelines, Data Engineering, Data Cleaning, Data Validation, Data Wrangling, Data Transformation, Feature Engineering, Feature Store, Data Lake, Data Warehouse, Data Modeling, Data Governance, Data Quality, Data Catalog.

Machine Learning, Artificial Intelligence (AI), Generative AI, Deep Learning, Large Language Models (LLMs), Small Language Models (SLMs), Open-Source LLMs, Retrieval-Augmented Generation (RAG), Agentic AI, AI Agents, Multi-Agent Systems, Prompt Engineering, Prompt Chaining, Fine-Tuning, Parameter-Efficient Fine-Tuning (PEFT), LoRA, QLoRA, RLHF, Model Distillation, Transfer Learning, Embeddings, Semantic Search, Vector Search, Vector Databases, Hybrid Search, Knowledge Graphs, NLP, NLU, NLG, Transformer Models, BERT, RoBERTa, GPT, Llama, Mistral, Gemma, Falcon, Phi, T5, Encoder-Decoder Models, Tokenization, Attention Mechanism, Computer Vision, CNN, RNN, LSTM, GRU, GANs, Autoencoders, Diffusion Models, Speech Recognition (ASR), Text-to-Speech (TTS), OCR, Recommendation Systems, Time Series Forecasting, Reinforcement Learning.

Scikit-learn, TensorFlow, Keras, PyTorch, Hugging Face Transformers, Hugging Face Hub, LangChain, LlamaIndex, DSPy, Haystack, OpenAI API, Azure OpenAI, Anthropic Claude API, Google Gemini API, Cohere, Ollama, vLLM, MLflow, Weights & Biases (W&B), ONNX, ONNX Runtime, TensorRT, XGBoost, LightGBM, CatBoost, Statsmodels, Prophet, FAISS, ChromaDB, Pinecone, Weaviate, Milvus, pgvector, Elasticsearch, OpenSearch.

Model Development, Model Training, Model Evaluation, Model Validation, Hyperparameter Tuning, Cross Validation, Model Optimization, Model Compression, Quantization, Pruning, Batch Inference, Online Inference, Real-Time Inference, Distributed Training, Distributed ML, Explainable AI (XAI), Model Interpretability, Model Monitoring, Drift Detection, Bias Detection, Responsible AI, AI Governance, Guardrails, Human-in-the-Loop (HITL), Experiment Tracking, A/B Testing, Feature Importance, SHAP, LIME, Model Lifecycle Management, MLOps.

AWS, Microsoft Azure, Google Cloud Platform (GCP), Amazon EC2, AWS Lambda, Amazon ECS, Amazon EKS, AWS Fargate, AWS Batch, Amazon S3, Amazon RDS, Amazon Aurora, Amazon DynamoDB, Amazon Neptune, Amazon Redshift, AWS Glue, AWS Step Functions, Amazon SageMaker, AWS Bedrock, Azure Machine Learning, Azure AI, Azure OpenAI Service, Azure Functions, Azure Data Factory, Azure Blob Storage, Azure Cosmos DB, Azure Kubernetes Service (AKS), Google Kubernetes Engine (GKE), Google Vertex AI, Google BigQuery, Google Cloud Storage (GCS).

PostgreSQL, MySQL, SQL Server, Oracle Database, SQLite, MongoDB, Cassandra, Redis, DynamoDB, Aurora, Snowflake, Neo4j, Amazon Neptune, Elasticsearch, OpenSearch, ChromaDB, Pinecone, Weaviate, Milvus, pgvector, Cosmos DB, Vector Databases.

Docker, Kubernetes, Helm, Docker Compose, Terraform, Pulumi, AWS CloudFormation, AWS CDK, Bicep, Ansible, Jenkins, GitHub Actions, GitLab CI/CD, Azure DevOps, Flux GitOps, ArgoCD, CI/CD Pipelines, Infrastructure as Code (IaC), Git, GitHub, GitLab, Bitbucket, SonarQube, Liquibase.

Linux, Unix, Windows Server, Nginx, Apache HTTP Server, RabbitMQ, Apache Kafka, ActiveMQ, MQTT, Redis Streams, Event Streaming, Message Queues, Cron Jobs, Load Balancing, Reverse Proxy, High Availability, Scalability, Performance Optimization, Caching, CDN, Observability.

Prometheus, Grafana, Datadog, Splunk, ELK Stack, OpenTelemetry, CloudWatch, Azure Monitor, PagerDuty, Logging, Monitoring, Alerting, Distributed Tracing, Application Performance Monitoring (APM), Incident Management.

PyTest, Unit Testing, Integration Testing, Functional Testing, End-to-End Testing, Test Automation, Mocking, Coverage, Selenium, Playwright, REST Assured, BDD, Cucumber, TDD.

React.js, JavaScript, TypeScript, HTML5, CSS3, Bootstrap, Tailwind CSS, Angular, Vue.js, Streamlit, Gradio, Jupyter Notebook, JupyterLab.

Agile, Scrum, Kanban, SDLC, Architecture Design, System Design, Solution Architecture, Technical Leadership, Code Reviews, Mentoring, Stakeholder Management, Technical Documentation, Production Deployment, Release Management, DevSecOps, Secure Coding, Healthcare, Life Sciences, Payer Systems, Provider Systems, Digital Transformation, Intelligent Automation, Business Process Automation, ArcGIS Python API, Spatial Data Analytics, GIS, Computer Vision, Statistics, Probability, Linear Algebra.

About

• 11+ years of experience as a Lead Python Developer/AIML designing and developing scalable enterprise applications using Python, FastAPI, Django, ORM, REST APIs, Microservices, AWS, Azure, GCP, Docker, Kubernetes, Kafka, PostgreSQL, MongoDB, React.js, AI/ML, Chatbots, ETL, Delta Lake, PySpark, Terraform, Jenkins, Git, and CI/CD.
• Proficient in developing scalable backend applications using Python, Django, FastAPI, Flask, PostgreSQL, MySQL, MongoDB, Redis, REST APIs, Docker, Kubernetes, Git, Jenkins, Terraform, AWS Lambda, and Microservices while maintaining performance, reliability, and security standards.
• Experience in Python application development by designing scalable Microservices, REST APIs, FastAPI, Django, Node.js integrations, ETL pipelines, Delta Lake, PySpark workloads, and cloud-native deployments across AWS, Azure, GCP using Docker, Kubernetes, Git, and CI/CD.
• Expertise in backend solutions using Python, FastAPI, Django, ORM, PostgreSQL, MongoDB, MySQL, Kafka, Pub/Sub, Redis, Snowflake, Databricks, AI/ML, Chatbot integrations, Terraform, Docker, Kubernetes, and automated CI/CD pipelines for highly available distributed systems.
• Experience in developing secure, high-performance REST APIs and Microservices using Python, FastAPI, Flask, Django, GraphQL, API Gateway, PostgreSQL, MongoDB, Redis, MySQL, Kafka, AWS Lambda, Docker, Kubernetes, Terraform, Jenkins, Git, and cloud-native deployment strategies.
• Expertise in building modern full-stack enterprise applications using Python, React.js, Angular, Node.js, HTML, CSS, JavaScript, FastAPI, REST APIs, PostgreSQL, MongoDB, AI/ML, Chatbots, Docker, Kubernetes, Azure DevOps, and Git-based CI/CD workflows.
• Experience in designing large-scale ETL and data engineering solutions using PySpark, Apache Airflow, AWS Glue, Databricks, Delta Lake, Snowflake, BigQuery, Kafka, MySQL, Pub/Sub, GCS, S3, Python, SQL, Terraform, and cloud-native orchestration across AWS, Azure, and GCP.
• Experience in implementing AI/ML-powered enterprise platforms using Python, Pandas, NumPy, PyTorch, Scikit-learn, LLMs, Chatbots, FastAPI, Vector-based integrations, REST APIs, PostgreSQL, MongoDB, Docker, Kubernetes, AWS, Azure, and GCP services.
• Expertise in modernizing legacy enterprise platforms by migrating monolithic applications to Python-based Microservices using FastAPI, Django, Node.js, React.js, Kafka, PostgreSQL, MongoDB, Docker, Kubernetes, Terraform, Jenkins, MySQL, and GitOps-driven CI/CD automation.
• Experience in collaborating with cross-functional teams to deliver enterprise software using Python, FastAPI, Django, React.js, Angular, HTML, CSS, JavaScript, PostgreSQL, MongoDB, Kafka, Pub/Sub, Docker, Kubernetes, Jenkins, Git, Agile, and DevOps best practices.
• Expertise in optimizing application performance through programming, multithreading, multiprocessing, Redis caching, Kafka messaging, PostgreSQL, MongoDB optimization, PySpark processing, ETL enhancements, Delta Lake optimization, and Kubernetes resource management.
• Experience in leading the design and development of Python applications by building FastAPI and Django Microservices, implementing secure REST APIs, integrating Kafka and Pub/Sub for event-driven communication, and deploying cloud-native solutions across AWS, Azure, and GCP.
• Expertise in designing high-performance ETL frameworks using PySpark, Apache Airflow, AWS Glue, Databricks, and Delta Lake to ingest, transform, validate, and process large-scale structured and unstructured datasets while improving data quality and reducing processing time.
• Experience in developing responsive full-stack applications using React.js, Angular, PostgreSQL, HTML, CSS, JavaScript, and Node.js by integrating reusable UI components with Python backend services, enabling seamless user experiences and efficient communication through REST APIs.
• Expertise in designing secure backend services by implementing JWT authentication, role-based authorization, API Gateway policies, MySQL, AWS IAM, Azure AD, and encrypted REST APIs, ensuring compliance with enterprise security standards and protecting sensitive business data.
• Experience in developing scalable data-driven applications using PostgreSQL, MongoDB, MySQL, Redis, and SQLAlchemy by designing optimized database schemas, indexing strategies, caching mechanisms, and high-performance queries to support business-critical transactional workloads.
• Expertise in implementing real-time data streaming architectures using Kafka, Google Pub/Sub, ORM, and Apache Storm to process high-volume event streams, enable asynchronous communication between Microservices, and deliver reliable, fault-tolerant business workflows.
• Experience in automating CI/CD pipelines using Jenkins, GitHub, Angular, Azure DevOps, Terraform, and Docker by streamlining build, testing, infrastructure provisioning, and deployment processes, significantly reducing release cycles and improving software delivery reliability.
• Expertise in building enterprise reporting and analytics platforms by integrating Snowflake, BigQuery, Databricks, Delta Lake, and PySpark, enabling efficient data transformation, business intelligence reporting, and high-performance analytical workloads for large-scale datasets.
• Experience in modernizing applications by migrating monolithic systems into Python-based Microservices using FastAPI, Django, Node.js, Docker, and Kubernetes, improving scalability, deployment flexibility, and overall application performance without disrupting business operations.
• Knowledge of designing secure cloud-native architectures using Java, FastAPI, REST APIs, AWS IAM, PostgreSQL, Azure AD, RBAC, API Gateway, Lambda, Kubernetes, Docker, Terraform, CloudFormation, Azure Bicep, monitoring, logging, and enterprise governance best practices.
• Expertise in optimizing application performance by implementing asynchronous Python programming, multithreading, multiprocessing, Redis caching, database query optimization, and efficient API response handling to support high-concurrency applications with minimal latency.
• Knowledge of implementing comprehensive testing, monitoring, and observability using PyTest, MySQL, Unit Testing, BDD, CloudWatch, Stackdriver, Grafana, Azure Monitor, GitHub, Angular, Jenkins, Docker, Kubernetes, and automated deployment across multi-cloud environments.