Top Python Developer Jobs in Delhi

Design, implement, and maintain scalable, secure GCP infrastructure and Kubernetes deployments. Build and optimize CI/CD pipelines (Jenkins), automate IaC (Terraform/Deployment Manager), monitor systems (Prometheus, Grafana, Cloud Monitoring, ELK), troubleshoot production issues, apply SRE practices (SLIs/SLOs, incident management), and harden Linux-based environments.

Build modular agentic components and integrate memory layers, tool integrations, MCP servers, and skills. Own feature quality with tests, evals, and observability. Debug production traces, improve retrieval and LLM pipelines, and collaborate on agent orchestration for proposal automation in the AEC industry.

Lead backend architecture and engineering: design scalable APIs and services, mentor engineers, write complex code, enforce best practices for databases, testing, observability, and integrate ML/LLM workloads.

The Senior Full Stack Engineer will design and maintain features across backend and frontend systems, focusing on scalability and security while collaborating on production-grade solutions in a fast-paced environment.

Design, build, and deploy machine learning models for a payments platform, overseeing end-to-end solutions and experimentation, while monitoring models in production.

The Senior Analyst will own Pricing Tools, manage data governance, drive pricing strategy decisions, execute audits, and enhance operational effectiveness.

As a Forward Deployed Engineer, drive customer success through AI deployments, optimize systems for reliability, and collaborate with teams to enhance products.

As a Strategic Projects Lead, you will manage high-impact AI data initiatives, optimize operations, and enhance customer relationships while collaborating with various teams to drive revenue growth.

As a hands-on data engineer, you'll build and enhance scalable data platforms, develop data pipelines, and collaborate with various teams to improve data solutions and system performance.

As a Software Engineer at Canonical, you will design, build, and ship software, improve packaging and distribution processes, and mentor colleagues while contributing to open source projects.

The Junior Ubuntu Software Engineer will design, build, and ship software, focusing on quality and resilience, while engaging with the open source community.

The Ubuntu Engineering Lead will oversee and mentor teams, drive the development and delivery of high-quality software, and contribute to community engagement while managing technical roadmaps and cultivating engineering talent.

Seeking a Senior SDET to ensure quality of large-scale data systems, focusing on test automation, performance tuning, and collaboration with teams. Responsibilities include creating test plans, automating tests, and enhancing testing processes.

Plan and implement QA procedures for enterprise releases. Create and execute manual and automated test plans, automate test suites, analyze features, report metrics, participate in Agile scrums, and collaborate with product owners and developers on requirements and acceptance criteria.

Plan and implement QA procedures for enterprise releases; create and execute manual and automated test plans (including Selenium); automate test suites; analyze features for test approaches; participate in Agile scrums; collaborate with product owners and developers to define requirements and acceptance criteria; gather metrics and report test results.

Design and build web and mobile applications across backend and frontend stacks. Write high-quality code, develop large-scale projects, collaborate with cross-functional teams, manage projects using tools like JIRA, and troubleshoot application and environment issues.

Design, develop, and maintain GIS databases; perform spatial analysis and cartography; create maps, visualizations and reports; manage spatial data and databases; automate GIS workflows with scripting; collaborate with cross-functional teams to support business decisions.

Support threat intelligence, incident analysis/response, penetration test coordination, vulnerability scanning and remediation tracking, security tool administration, dashboard maintenance, and adherence to security policies while learning and developing cybersecurity skills.

Lead application security efforts by governing vulnerability management, automating security workflows, embedding SSDLC practices, partnering with engineering/GRC to meet compliance, and serving as a security SME during incident response and customer escalations.

Design and execute ETL test plans to validate extraction, transformation, and loading processes. Perform source-to-target SQL validations, data reconciliation, regression and integration testing, monitor ETL jobs, report defects, and collaborate with engineers and analysts to ensure data quality and governance.

Maintain and optimize production LLM/VLM services and microservices (Flask/FastAPI), manage async queues, deploy and monitor Uvicorn/Gunicorn hosts, integrate LLM routing tools, design prompt strategies, build feedback/evaluation pipelines, expose secure REST APIs, and track token usage, latency, and errors to ensure SaaS-grade AI performance.

Own data quality and root-cause analysis for prediction issues: detect anomalies, trace sources, fix processes, automate QA/reporting with Python and SQL, maintain dashboards, and partner with Data Science, Engineering, Product, and Commercial teams to improve prediction performance and customer-facing analytics.

Support data integrations and quality by checking ingested/system-generated data for anomalies, building and running QA checks and automations with Python and SQL, assisting on customer data queries and dashboards, and documenting findings to improve prediction reliability.

Lead design and delivery of end-to-end prototypes and production-ready solutions for emerging AI initiatives. Drive AI R&D, mentor engineers, establish engineering standards, communicate architecture to stakeholders, and enable rapid experimentation amid high ambiguity.

Build and productionize ML systems for personalization, search, and recommendations. Apply statistical and ML models using Python and SQL, collaborate with stakeholders, and measure business impact across cloud environments.