Top Python Developer Jobs in Delhi

Leads end-to-end data products from ingestion and transformation through semantic modeling, Power BI reporting, documentation, governance, and user adoption. Builds Microsoft Fabric pipelines, Lakehouse or Warehouse architectures, dimensional models, and secure, optimized Power BI solutions. Analyzes data, supports advanced analytics and AI-assisted reporting, establishes quality and CI/CD practices, collaborates with cross-functional stakeholders, and manages data engineers through objectives, reviews, and development.

Designs and implements computer vision and machine learning algorithms for aquaculture applications. Responsibilities include developing prototypes, conducting experiments, building data-processing and training pipelines, maintaining model testing and statistical verification, extending AI codebases, documenting research, leading long-term research, recruiting talent, and tracking AI developments. The role may also involve production deployment, inference optimization, MLOps, cloud platforms, and occasional visits to aquaculture sites.

Responsible for black-box testing and verification of MaxScale across many configurations, managing packaging and quarterly releases, maintaining automated build infrastructure, troubleshooting builds, reproducing customer issues, and contributing test cases or fixes. Works closely with support, development, and release teams.

Participate in cryptography research for blockchain applications, focusing on post-quantum signatures, threshold signatures, signature aggregation, and proof systems. Benchmark NIST PQ standards, collaborate with senior researchers to apply results, publish findings, and contribute to open-source projects.

Analyze EMEA marketing performance across B2B and B2C funnels, identify trends and opportunities, and provide evidence-based recommendations to marketing leadership. Collaborate with Sales, Product, Finance, and customer engagement teams to improve strategy and revenue outcomes. Build reports and presentations that translate complex data into actionable insights, champion advanced analytics and marketing technology, and support innovation across global marketing practices.

Provides customer-facing technical support by owning tickets from intake through resolution, meeting SLAs, troubleshooting data quality and integration issues, documenting solutions, and coordinating escalations. The role also contributes to knowledge management, pipeline monitoring, dashboards, AI agents, and workflow automation. Success requires accuracy, customer empathy, strong communication, systematic problem-solving, and the ability to manage multiple priorities in a remote, fast-paced SaaS environment.

Build and support DevOps capabilities using Kubernetes, AKS, Azure, Git, ARM templates, scripting, CI/CD pipelines, Azure DevOps, GitHub Actions, Ansible Tower, and Terraform. Apply container orchestration, networking, and Agile methodologies to automate and manage cloud infrastructure and software delivery.

Lead and grow an SDET team, define functional testing strategy and infrastructure, champion AI/LLM-driven test generation, maintenance, and analysis, own deployment and CI/CD for production services in containerized AWS environments, perform code reviews, and collaborate with product and engineering to ensure release quality.

Build the AI layer for SigNoz: implement agent orchestration, long-running execution, streaming APIs (SSE), and MCP server integrations to expose observability data to LLM agents. Ship production LLM features, design scalable distributed backends in Go and async Python, and drive projects end-to-end in a remote-first environment.

Architect and build a scalable, production-ready, multi-tenant ecommerce SaaS platform. Define architecture and technical standards, implement backend and frontend (Python/React), design APIs, ensure reliability, security, observability, and drive CI/CD, DevOps, and best practices while mentoring engineering teams.

Design, develop, and deploy generative AI agents and end-to-end ML pipelines. Lead prompt engineering, LLM integration, model training, and productionization, collaborating with customers and stakeholders to deliver AI solutions.

The Site Reliability Engineer will provision and manage Kubernetes clusters, build automation tools, debug customer issues, and improve infrastructure reliability.

Implement, test, and deliver assigned features within sprints; write clean, well-documented code; participate in code reviews; collaborate with seniors, QA, and product; learn new tools and contribute to improving codebase and processes.

Deliver end-to-end features for microservices-based systems, focusing on reliability, performance, testing, and production troubleshooting. Collaborate with product, QA, and DevOps, mentor junior engineers, adopt AI-assisted development, and improve system stability and delivery practices.

Lead architecture and delivery of scalable, secure web applications; drive AI-first engineering and LLM integrations; write full-stack production code; mentor engineers; promote best practices in microservices, cloud-native, CI/CD, observability, and security.

Develop RTL for digital blocks, perform lint/CDC analysis and DFT support, assist in writing functional tests and simple UVM components, collaborate on verification and coverage closure, support AMS co-simulation and mixed-signal integration, and work with physical design on synthesis and timing.

As a Senior Agentic AI Lead, you will manage the agentic AI domain, engage with customers, oversee the AI lifecycle, and ensure effective data governance and analytics across various teams.

Perform satellite image classification and time-series analysis using Sentinel and PlanetScope data; build and optimize ML classification pipelines; develop Google Earth Engine apps and geospatial tools; apply advanced geospatial and hydrological modelling; coordinate ground-truth collection; produce reports, research papers, and decision-support dashboards; support stakeholder engagement.

As a Helix Administrator, you will manage and optimize Helix environments, oversee code repositories, implement CI/CD best practices, and provide user support.

The Aveva PI Software Engineer designs and maintains Aveva PI systems, collaborates with teams for data integration, monitors performance, and creates analytical dashboards.

Design and implement Helix integration and automation solutions, enhance productivity through workflows, and troubleshoot integration issues while collaborating with clients.

Architect and implement OpenBMC-based management for server platforms integrating BMCs, host CPUs, and top-of-rack Ethernet switches. Develop D-Bus services, Redfish APIs, object models, telemetry, security, firmware, and L2 networking capabilities. Build backend abstractions supporting switchdev, SAI, SONiC, DENT, and vendor SDKs. Collaborate across hardware, security, firmware, QA, manufacturing, and networking teams to deliver reusable, testable platform-management architecture.

Administer and architect enterprise Atlassian solutions across Jira Software, Jira Service Management, and Confluence. Configure workflows, permissions, automations, dashboards, and integrations with Microsoft 365, CI/CD pipelines, and business systems. Develop API and scripting solutions, maintain platform stability and documentation, establish governance standards, and advise stakeholders on platform strategy, best practices, security, and continuous improvement.

Lead the design, development, and delivery of backup, restore, replication, and continuous data protection capabilities. Architect storage-driver interfaces and storage-independent replication for reliable recovery across data centers. Mentor engineers and provide technical direction across engineering, QA, UI, and UX. Collaborate with Product and Support, troubleshoot distributed-system failures, lead root-cause analysis, and establish engineering practices for testing, automation, documentation, and operational readiness.

Lead full-stack development using Python and FastAPI; build high-performance APIs integrated with AWS (SQS, Lambda). Implement front-end using React/Angular, manage Mongo/MySQL/Oracle databases, integrate AI features via prompt engineering and GitHub Copilot/Cursor, optimize performance, apply DevOps/CI-CD, troubleshoot and collaborate in Agile/Scrum with Jira and Git.