Top Python Developer Jobs in Delhi

The Senior Product Analyst will automate data collection, analyze product metrics, conduct A/B tests, and support product hypothesis generation.

The Data Engineering Lead oversees data engineering operations, manages teams, ensures data integrity, and drives innovation in data management and governance.

The Security Engineer will enhance security operations capabilities, manage vulnerabilities, oversee security tooling, and develop automation for security workflows.

The Technical Support Engineer will assist customers with issues related to YugabyteDB, troubleshoot technical problems, and collaborate with other teams to meet customer needs.

The role involves leading actuarial projects, managing client communication, and collaborating with teams to deliver actuarial solutions in a fintech environment.

The Senior Site Reliability Engineer ensures the availability, performance, and security of Drivetrain's SaaS platform, managing multi-cloud infrastructure, optimizing CI/CD pipelines, and driving automation.

The Senior Emulation Engineer will validate AI accelerator architectures, maintain emulation platforms, develop testbenches, and collaborate on performance optimization and debugging processes.

Design, build, and maintain fullstack web systems with Zoom Apps integration. Implement scalable front-end and back-end components, APIs, and cloud-hosted services while optimizing performance and collaborating with product and research teams in a fast-paced health-tech startup.

Operate and administer cloud infrastructure (Google Cloud, AWS), automate tasks with Python/Scala, manage containers (Kubernetes/Docker), design/maintain IaC, troubleshoot systems and networks, perform root-cause analysis, improve resiliency, document processes, advise clients, and participate in on-call rotations.

Own and grow automated test coverage for backend and frontend, integrate tests into CI, build outbound-call automation through the live voice pipeline, measure STT/TTS accuracy, evaluate conversational quality, reproduce and track defects, and collaborate with engineers, prompt authors, and operations to prevent regressions.

Design, build, and maintain scalable ETL pipelines and data models for analytics and ML. Ensure data quality, optimize performance, enforce governance and security, and collaborate with stakeholders to deliver reliable, production-ready data for reporting and data science.

Lead design, development, and deployment of production-ready ML/AI systems using Python, PyTorch, LLMs and related tools. Drive model research, tuning, monitoring, cross-functional integration, and mentor junior engineers while prioritizing practical business impact.

Design, deploy, and maintain scalable cloud infrastructure across AWS/Azure/GCP. Build and operate CI/CD pipelines (GitLab/GitHub Actions), automate provisioning with Terraform/CloudFormation, use Python for automation, monitor performance and security, troubleshoot deployments, enforce compliance and DR policies, and optimize cloud costs.

Design and build scalable backend systems and AI-powered solutions (LLMs, RAG, retrieval, agents). Own projects end-to-end, optimize performance, drive AI engineering standards, mentor engineers, and integrate AI with enterprise systems.

Lead architecture and delivery of enterprise Generative AI solutions: design LLM-based RAG pipelines, multi-agent systems, and secure cloud deployments; establish LLMOps best practices; advise clients, run PoCs, and mentor engineering teams to operationalize scalable, compliant AI systems.

Develop, train, evaluate, and optimize ML solutions and data pipelines; translate business requirements into production-ready ML code; perform feature engineering, model selection, and evaluation; document work, participate in code reviews, and support testing and data issue resolution.

Investigate escalated production incidents (DB anomalies, failed payments, data migrations), write post-mortems and runbooks, and build AI-powered automation (LLM diagnostics, agents) plus developer tooling. Maintain CI/CD, GCP infrastructure, container deployments, observability, and partner on ERP and payment provider integrations.

Lead backend QA efforts across the SDLC: design and execute test plans and automation, validate APIs, databases and distributed services, track defects, and improve test strategy to reduce manual effort.

Early-career TechOps role in Binance Accelerator Program focused on observability, automation, and AIOps foundations. Build dashboards, alerts, runbooks, automate repetitive support tasks, perform RCAs, prototype lightweight agents/skills, and improve incident management workflows. Hands-on with logging/metrics/traces, basic MLOps concepts, and support-driven product improvements.

Tier 3 Technical Support Engineer responsible for advanced troubleshooting of distributed trading/payment systems, collaborating with DevOps and backend teams, building automation tools, dashboards, and incident management processes, and supporting Java/Spring Boot microservices and blockchain infrastructure to ensure 24/7 platform stability.

Manage post-listing partner and operational requests (rebranding, token swaps, mainnet integration, airdrops), perform ROI and risk analyses, run projects through SOP stages, build risk-control systems, optimize processes, support analytics and post-mortems, and deliver initiatives on time.

Design, deploy, and maintain blockchain infrastructure and cloud services on AWS. Administer and scale EKS Kubernetes clusters, build CI/CD pipelines (GitHub Actions, ArgoCD, CodeBuild), and automate infrastructure with Terraform/CloudFormation and Helm. Monitor system performance, tune services, and collaborate with global partners.

Design, build, and maintain internal developer tools, backend services, and automation to improve engineering efficiency. Integrate tools with CI/CD and cloud platforms, diagnose and fix tooling issues, research new tooling approaches, and ensure platform scalability, reliability, and maintainability.

Develop and refine voice-optimized prompts and agentic LLM workflows for finance use cases. Build RAG grounding, integrate LLMs with voice/telephony (LiveKit), implement feedback loops, A/B testing, fine-tune models, and collaborate on production ML services and OCR/chatbot components.

Provide Tier 3 technical support for large-scale trading systems, troubleshoot distributed backend and blockchain issues, collaborate with developers/DevOps, build automation tools, dashboards, and monitoring, document root causes, and support 24/7 incident management for Binance's platform.