Top Python Developer Jobs in Delhi

The Azure DevOps Engineer will design and build scalable systems, implement CI/CD, create monitoring solutions, and support application health, among other tasks.

Develop and manage web applications using the MEAN stack, create APIs, and ensure quality releases while collaborating in an Agile environment.

Design, develop, test, and deploy scalable web applications across front-end and back-end stacks. Build responsive UIs, develop APIs/microservices, integrate third-party/cloud services, optimize performance, troubleshoot and upgrade systems, participate in code reviews and agile processes.

Design, build, and maintain scalable Python backend services using AWS (Lambda, EC2, S3, DynamoDB, API Gateway). Develop RESTful APIs, optimize performance, collaborate on CI/CD and deployment automation, use IaC (CloudFormation/Terraform), containerize with Docker and orchestration (ECS/EKS), mentor junior developers, and participate in agile processes.

Design, develop, and maintain automated testing frameworks and scripts using Python and Pytest. Integrate automated tests into CI/CD pipelines, analyze application flows, identify and report issues, collaborate with cross-functional teams, and apply OOP, code reusability, and fuzzy logic to improve test coverage and reliability.

Develop and maintain Python backend components, design and optimize SQL for large datasets, perform ETL, integrate front-end and third-party services, troubleshoot applications and databases, ensure data quality and security, participate in code reviews, and produce technical documentation.

Design and implement scalable cloud-native data and analytics platforms (AWS/Azure) using Databricks, Snowflake, SQL, Python/PySpark. Build ingestion, ETL/ELT, orchestration, integration, and reporting pipelines. Support data modeling, analytics-ready structures, BI tools, CI/CD, deployments, production support, incident management, and AI/ML-enabled analytics. Collaborate with architects, stakeholders, and engineering teams to drive standards, governance, and operational excellence.

Develop and maintain backend applications using Python and Django. Architect and implement microservices, migrate monolithic systems to microservices, build RESTful APIs, optimize performance and security, collaborate with DevOps/frontend/QA, and troubleshoot production issues.

Deploy and productionize ML models on GCP Vertex AI for real-time and batch inference. Build scalable pipelines, perform feature engineering, monitor model performance and drift, support ML-Ops and governance, and collaborate with teams on retail banking (credit risk, marketing, customer service) use cases.

Lead development of GenAI and LLM-powered applications using Python, LangChain/LangGraph and FastAPI. Design scalable cloud-ready microservices, integrate LLMs (AWS Bedrock/OpenAI), implement prompt engineering, and build interactive frontends with Angular/JavaScript. Ensure AWS-based deployment and database integration (SQL/NoSQL).

Develop and maintain scalable backend systems with Python (Django/Flask), build responsive front ends with React or Angular, integrate AI/ML components, ensure performance and security, participate in architecture and code reviews, and collaborate with cross-functional Agile teams.

Lead design and delivery of NLP and Generative AI solutions, from problem definition through deployment. Build and fine-tune transformers and LLMs for summarization, QA, classification and chatbots, apply classical and deep learning methods, ensure scalable reproducible ML workflows in cloud environments, mentor junior data scientists, and collaborate with product and engineering to translate business problems into AI solutions.

Lead hands-on development of enterprise AI features: prototype with modern LLM tools, implement prompt engineering, RAG, and function calling, collaborate closely with engineers through design, code reviews, and sprints, own delivery timelines, and balance technical debt, scalability, and security for B2B products.

Design and implement AI/LLM-driven data extraction and ETL pipelines, build web crawling and API integrations, implement RAG systems, mitigate LLM hallucinations, evaluate third-party tools, and collaborate with content and analytics teams to deliver high-quality, scalable data for downstream analysis.

Design and implement Python-based automated UI and API tests using Selenium, Pytest, Rest Assured or Postman. Validate data with SQL, maintain test environments, collaborate with development and QA, analyze results, and report defects to ensure high-quality deliveries.

Design, deploy, and operate highly available AWS infrastructure using IaC. Build and manage production Kubernetes clusters, implement cloud security and compliance, set up observability with Grafana/Kibana, automate via scripting and CI/CD, troubleshoot high-traffic issues, and collaborate across teams to continuously improve reliability and scalability.

Build backend systems on the Internet Computer using Rust, compile to WebAssembly, apply TDD for unit and integration tests, maintain Git-based deploy workflows, create CI/CD pipelines with GitHub Actions (canary/staging), and operate with strong ownership, fast decision-making, and ability to work under pressure.

Lead delivery of data and digital consulting services: define deliverables, engage senior stakeholders, manage small teams, design scalable data pipelines, implement dashboards and analytics, ensure data quality and governance, and drive digital transformation using cloud, BI, and automation tools.

Build and operate backend services and infrastructure for LLM- and voice-driven healthcare applications. Implement APIs, productionize LLM workflows, deploy cloud containerized services, and monitor performance and reliability end-to-end.

Create and own technical content (blogs, tutorials, demos, video) for Altimate Code. Generate ideas tied to the modern data stack, deeply test the product, support SEO/AEO, build editorial workflows, and distribute content across developer channels.

Lead statistical programming for sponsor clinical trials: develop SDTM/ADaM specs and datasets, author validated SAS/R programs, oversee CRO deliverables, support regulatory submissions, and maintain programming standards and SOPs.

Lead technical direction and implementation across the team from design through deployment. Drive architecture decisions, code reviews, documentation, and mentoring. Ensure secure, scalable, high-performance enterprise systems, collaborate with product and design, validate architecture implementations, and support CI/CD and repository practices.

Develop, deploy, and scale AI/ML and generative AI solutions for a fintech platform. Design data models and pipelines, build agentic frameworks, integrate OCR and vector DBs, implement RAG, and champion MLOps and cloud deployment practices while mentoring teammates.

Operate and scale low-latency, high-availability trading infrastructure; automate and manage IaC; monitor and respond to incidents; optimize system and network performance; implement secure CI/CD and IAM practices; collaborate with trading, engineering, and security teams; participate in rotational on-call support.

The Customer Support Engineer will resolve technical challenges for customers involving AI solutions, collaborating with internal teams to improve offerings and ensure customer satisfaction.