Top Python Developer Jobs in Delhi

Build and manage AWS infrastructure, Kubernetes deployments, GitOps CI/CD pipelines, data stores, observability systems, and incident response processes. The role supports multiple engineering and data teams, including managing MongoDB and Elasticsearch clusters, Grafana and Prometheus monitoring, IAM services, and scalable, highly available cloud-native systems.

Own measurement and reporting for an AI product portfolio. Responsibilities include defining metrics, running business reviews, building Superset dashboards, querying ClickHouse and Snowflake, analyzing retention and adoption, calculating AI usage economics, evaluating product quality, reconciling data sources, and informing roadmap decisions through instrumentation, experimentation, and product analytics.

Lead QA automation strategy and build end-to-end test frameworks for web, API, and AI-driven features. Develop UI and API automation, performance/load tests, CI-integrated quality gates, and deterministic validation for non-deterministic ML outputs. Partner with product and engineering to define acceptance, shift-left quality, and validate AI/vision outputs and generated test code.

Build and maintain security automation solutions, reusable components, playbooks, apps, and dashboards for Swimlane Turbine and its Marketplace. Translate SOC and MSSP workflows into configurable enterprise content, normalize security data using Python and JavaScript, integrate SIEM, EDR/XDR, identity, threat intelligence, ticketing, and cloud security tools, and incorporate controlled AI-assisted workflows. Own testing, documentation, versioning, release quality, and cross-functional collaboration.

Build scalable, high-performance backend systems using primarily Golang and Python. Own features end to end, contribute to distributed microservices architecture and system design, develop event-driven components for high-volume messaging and e-commerce workloads, conduct code reviews, troubleshoot production issues, support CI/CD deployments, and document technical specifications and APIs.

Build and deploy production AI systems across LLM orchestration, retrieval, agents, evaluations, voice, APIs, backend services, and infrastructure. Design reliable LLM pipelines, evaluation suites, data flows, and real-time multimodal experiences. Experiment with emerging models, debug issues across the stack, and communicate technical decisions clearly while owning projects from exploration through production iteration.

Work directly with pharmaceutical customers to understand workflows and design, prototype, integrate, and deploy AI-powered solutions. Translate ambiguous requirements into technical architectures, build Python-based integrations and data workflows, lead technical discovery and implementation workshops, debug APIs and cloud deployments, and collaborate with customer and internal engineering teams. Bring recurring customer needs to product and engineering while supporting regulated enterprise AI deployments.

Build production-grade AI applications for pharmaceutical commercial, medical, and patient workflows using LLMs, retrieval, agents, structured data, and multimodal AI. Develop scientific knowledge systems, evaluation frameworks, and reliable, safe AI solutions using healthcare and life sciences datasets. Collaborate with pharma customers and domain experts to translate complex workflows into scalable technical products.

Conduct primary and secondary research on India’s startup ecosystem, verify funding and financial data, and extract information from MCA filings. Maintain research databases, tagging frameworks, and data pipelines while supporting editorial, marketing, and product teams. Track IPOs, listed technology companies, and venture capital activity, and generate data-backed insights for reports and journalism. The role requires strong financial research, analytical, data management, and startup ecosystem knowledge.

Build production-grade agentic AI systems that reason, search, and execute workflows. Develop RAG pipelines, AI agents, semantic search layers, data processing solutions, dimensional data models, and scalable AI workloads. Work with structured and unstructured data, LLMs, vector databases, cloud infrastructure, CI/CD, and ML observability. Responsibilities include fine-tuning models, prompt engineering, optimizing context windows, and deploying reliable AI applications.

Own and improve the Command|Alert alerting platform, including rule evaluation, anomaly detection, event correlation, reliable Kafka and OpenSearch pipelines, and downstream notifications. Convert security and network telemetry into usable topologies and dependency maps, support LLM-based alert generation, resolve production issues, lead reliability improvements, deliver independent projects, and mentor engineers while shaping technical direction.

Own the technical infrastructure supporting a large-scale camera and sensor data ingest pipeline. Build and maintain ingest stations, tooling, hardware fleets, quality controls, media lifecycle standards, inventory processes, and reporting. Troubleshoot failures, ensure data integrity and chain of custody, automate workflows with Python and shell scripts, train operators, document procedures, and support field deployments.

Develop and maintain network inventory, monitoring, and topology features for the Skylar One platform. Troubleshoot Python and MySQL performance issues, implement backend features in Python, PHP, and MySQL, write unit tests, and support scalable multithreaded or multiprocess services. Collaborate with Product Management and engineering teammates while applying networking fundamentals, automation practices, software development lifecycle standards, and high-availability architecture principles.

Develops and validates clinical data visualizations, dashboards, tables, listings, and reports using SAS and business intelligence tools. Extracts, integrates, transforms, and analyzes clinical and operational data from EDC and other sources to support data review, reconciliation, quality control, and site performance monitoring. Gathers stakeholder requirements, trains users, supports workflow automation, maintains documentation, and ensures compliance with SOPs and regulatory guidelines.

Drive adoption of Databricks Genie across a regional territory through technical strategy, executive engagement, workshops, presentations, demos, and customer-facing collateral. Partner with Account Executives, GTM, Product, Engineering, GSIs, and consulting firms. Architect governed analytics solutions spanning semantic models, warehouses, metric layers, Lakehouse, and AI ecosystems; address governance and security concerns; resolve complex technical escalations; and provide roadmap feedback.

Designs scalable, secure, cloud-native technology solutions aligned with business goals. Responsibilities include architecture design, technology selection and integration, cloud and DevOps enablement, performance and security optimization, technical governance, stakeholder collaboration, troubleshooting, and emerging technology evaluation. The role requires enterprise experience and expertise in generative AI, RAG architectures, AWS, Azure, infrastructure as code, automation scripting, and modern software development methodologies.

Lead architecture and design for ANTHEM tooling solutions in Honeywell Aerospace. Collaborate with business and technical leaders to deliver scalable, secure, cloud-native software, guide teams, recruit and develop talent, and ensure system integration, validation, and compliance.

Lead embedded avionics software development and verification per DO-178B/C. Drive test architecture, tools, and processes; conduct PDR/CDR/TRR and audits; use C/C++/Python, debuggers, simulators, VectorCAST/Cover and MATLAB; apply GenAI/LLMs to automate tasks; evaluate new technologies; mentor engineers and manage cross-functional stakeholders to meet quality, cost, and schedule goals.

Lead embedded software development and verification for avionics programs following DO-178B/C. Drive common test architectures, tools, processes, and automation (including GenAI). Influence stakeholders, plan and execute project schedules, mentor engineers, evaluate new technologies, and ensure efficient test strategies using tools like debuggers, simulators, Vector Cast/Cover, and MATLAB.

Lead embedded software development and verification for DO-178B/C aerospace programs. Drive test architecture, tools, and processes; use C/C++/Python and MATLAB; apply debuggers, simulators, VectorCAST, and GenAI (LLMs/ChatGPT) to automate tasks. Conduct PDR/CDR/TRR/reviews, bench setup, audits, evaluate new technologies, influence software architecture, mentor engineers, and manage stakeholders to meet quality, cost, and schedule objectives.

Partner with cross-functional teams to design and execute quantitative analyses, experiments, forecasting, and visualizations that influence product and business strategy. Translate data into stories and actionable recommendations, measure impact, and present findings to senior leadership.

Design, develop, and maintain scalable Microsoft Fabric and Azure data solutions. Build Lakehouse, Data Warehouse, OneLake, ETL/ELT pipelines, data transformations, and integrations using Python, PySpark, SQL, and Fabric tools. Implement medallion architecture, optimize data models and workloads, establish data quality monitoring, and support CI/CD deployments. Collaborate with analytics and business teams to deliver enterprise-scale data platforms.

Develop scalable enterprise applications and REST APIs using Python or .NET/C#, integrate Azure and Microsoft Fabric services, build SQL-based data and ETL/ELT solutions, and support Lakehouse, OneLake, and Data Warehouse architectures. Integrate LLMs and RAG capabilities into enterprise applications, troubleshoot application and data-pipeline issues, and collaborate with product, data, AI, and business teams. Backend and integration development are the primary focus, with working knowledge of modern front-end frameworks expected.

Design, develop, operate, and optimize large-scale software-defined networking solutions for NVIDIA AI Cloud environments. Responsibilities include building OVS/OVN control and data plane software, Kubernetes networking services, observability systems, CI/CD pipelines, GitOps integrations, and secure gRPC/REST services. The role owns production reliability, incident response, performance tuning, and upstream open-source contributions while collaborating with SRE, DevOps, and network engineering teams.

Leads architecture, development, and innovation for OLT software platforms in fiber-based fixed access networks. Designs GPON/XGPON and Layer 2 networking solutions, including forwarding, multicast, QoS, and VLAN capabilities. Provides technical leadership, mentors teams, resolves complex telecom software issues, collaborates with Product Management, and supports large-scale deployments. Requires deep expertise in telecom access or core network products, network processors, packet processing, traffic engineering, data models, programming, and test automation.