Top Python Developer Jobs in Delhi

The Power BI Administrator will manage the Power BI environment, support governance, automate workflows, and ensure compliance with data standards. Responsibilities include overseeing deployment, troubleshooting issues, and mentoring stakeholders on BI best practices.

The Technical Specialist will design and develop high-performance software for OLT platforms, improve product scalability, and collaborate with teams to address customer needs and troubleshoot telecom software issues.

Maintain and extend TestComplete automation framework using Python and BDD. Build Azure DevOps YAML pipelines, work with SQL/MSSQL, and support test maintenance. Mentor and upskill team members via pair programming, pull request reviews, and demos to hand over automation to GFS team.

Customer-facing AI Engineer who designs, builds, and deploys production-grade LLM and agent-based solutions. Responsibilities include architecting agent systems, implementing RAG pipelines, integrating with platform signals and vector DBs, overseeing end-to-end ML lifecycle, writing clean Python code, and collaborating with customers and internal teams to ensure scalable, monitored deployments.

Principal Data Engineer responsible for building big-data solutions using PySpark and Databricks, writing and optimizing SQL, developing Python pipelines, and working with Hadoop/Hive, Git, Airflow/Dagster, and Azure.

Design, build, and maintain scalable ETL/ELT pipelines and data warehouses using Snowflake, AWS Glue, Python, and SQL. Optimize performance, implement CI/CD with Azure DevOps, ensure data quality and governance, collaborate with analytics teams, and troubleshoot pipeline issues.

Design, develop, and maintain generative AI-powered software systems and full-stack AI applications. Implement LLM integrations, RAG pipelines, orchestration with LangChain/LlamaIndex, vector DBs, cloud deployment, CI/CD, monitoring, and collaborate on product design and code reviews.

Design, implement, and maintain scalable Azure cloud infrastructure, CI/CD pipelines, and Kubernetes-deployed applications using Terraform and automation. Support ETL/data pipeline deployments and Snowflake integration, monitor and troubleshoot systems, enforce cloud security and governance, and collaborate with development, QA, and data teams to streamline releases.

Architect, build, and operate end-to-end AI automation systems: CLI frameworks, MCP servers, agent tooling, production pipelines, evaluation and monitoring. Own prompt and context engineering, multi-agent orchestration, integration with external tools, governance, and metrics to measure automation and business impact.

Design, develop, and deliver UiPath automation solutions (POCs to production). Gather and document process requirements with SMEs, participate in design sessions, and support mentoring of junior developers. Follow WonderBotz standards and best practices for RPA implementations.

Support software QA across applications: design and run manual and automated tests, build/maintain automation frameworks, perform API/backend/performance testing, validate requirements, log and triage defects, integrate tests into CI/CD, and collaborate with cross-functional teams to improve QA processes and documentation.

Perform manual and automated testing for web and data-driven applications. Design and maintain automation frameworks and test scripts, execute functional, regression, integration, API, and performance tests, validate backend/data integrity, log and triage defects, integrate tests into CI/CD, participate in Agile ceremonies, and collaborate with cross-functional teams to improve QA processes and documentation.

The Technical Lead will design and implement advanced AI systems, lead a team, drive the development of AI features, and ensure robust model performance through evaluations and optimizations.

Lead technical efforts in hypervisor and cloud integration, automate deployments, and present solutions at industry events, along with creating technical content.

Develop and maintain AI systems for a financial platform, focusing on LLM pipelines, ML model serving, backend integration, and collaboration with engineering teams.

The Senior System Software Engineer will lead BMC firmware development, system management software, and performance optimization on NVIDIA server platforms while ensuring software quality and security compliance.

Lead design, development, and deployment of scalable ML models and MLOps infrastructure on AWS (SageMaker). Build recommendation, fraud, and credit risk systems; implement monitoring, observability, CI/CD, and production support; mentor engineers and collaborate with product teams to deliver AI-driven features.

Build and ship responsive, high-performance web applications using React and TypeScript. Translate designs into accessible UI components, optimize performance, integrate with REST/GraphQL APIs, collaborate with product/design/backend teams, participate in code reviews, and contribute to frontend architecture, testing, and CI/CD. Support occasional backend tasks if needed.

Designs, builds, and optimizes machine learning models and infrastructure, develops production-grade ML services and data pipelines, conducts research and evaluation, implements LLM fine-tuning and RAG solutions, and partners cross-functionally to translate business requirements into deployable ML deliverables.

Analyze complex datasets using SQL, build dashboards in Tableau, perform statistical and predictive modeling with R or Python, identify process improvements, and collaborate with cross-functional teams to drive business decisions.

Analyze complex datasets to uncover insights and trends; design and build analytical logic, data models, and calculations; validate data and KPIs; collaborate with stakeholders, engineering, data science, and BI teams to deliver scalable analytics and business intelligence solutions.

Lead Egnyte's India-based Desktop Team building Windows and macOS native apps. Partner with Product across regions to set priorities, unblock engineers, drive quality, monitor performance, recruit, develop careers, and champion AI adoption across the desktop platform.

Perform application and network penetration testing across web, mobile, and APIs; embed AppSec into DevSecOps; build automation, tooling, and KPI dashboards; integrate security tools via APIs; drive remediation and secure coding practices across engineering teams.

Lead architecture, build, and scale Sleek's cloud infrastructure and AI-ready platform. Improve reliability, observability, CI/CD, IaC, security, and incident response. Integrate and support AI/ML workloads, mentor engineers, and drive DevOps and platform enhancements to increase velocity and operational excellence.

Build and maintain scalable cloud-native backend applications using .NET and Java/Python. Collaborate with cross-functional teams, apply TDD and unit testing, set up CI/CD pipelines, use Git for version control, and deploy on Azure/GCP/AWS while working with SQL Server and Entity Framework.