Top Python Developer Jobs in Delhi

Build, test, deploy, and maintain production automations using n8n, custom code, AI models, APIs, and PostgreSQL pipelines. Identify high-value automation opportunities, integrate unfamiliar systems, validate data integrity, manage CI/CD, monitor reliability and cost, respond to incidents, and resolve recurring failures. Collaborate with stakeholders and audit teams on security, compliance, and process quality while researching emerging automation and AI technologies.

Own the quality engineering strategy and platform across Android, web, API, and backend systems. Design and maintain comprehensive manual and automated testing for complex distributed architectures, lead root-cause analysis, define quality metrics, integrate testing into CI/CD, and certify releases and production hotfixes. Collaborate with product, engineering, and DevOps teams, conduct QA automation code reviews, identify production risks, monitor field issues, and mentor junior quality engineers.

Perform hands-on vulnerability triage and risk assessment across OS, containers, and dependencies; validate and reproduce customer and pentest findings; maintain and troubleshoot SAST/DAST and scanning pipelines; build PoC exploits to validate real-world risk; partner with Engineering to prioritize and ship fixes; improve vulnerability management processes and SLAs.

The role involves building and integrating LLM-powered systems, requiring expertise in Python, agent frameworks, and modern API development.

The QA Engineer will be responsible for planning and executing software testing, writing test cases, bug filing, and maintaining testing documentation.

Develop high-quality engineering solutions for Merch Tech tools, build workflows and APIs for merchants, and ensure fast iteration and ownership.

Designs and operates GCP or AWS infrastructure for AI, geospatial, and data-intensive workloads. Builds CI/CD pipelines, manages Docker and Kubernetes environments, supports ML training and inference, optimizes cloud costs, and maintains data pipeline infrastructure. Establishes monitoring, logging, alerting, IAM, secrets management, vulnerability scanning, and network controls. Supports API platforms and collaborates with AI, geospatial, and product teams to resolve deployment, scaling, and reliability issues.

Leads the architecture, development, deployment, and operation of scalable AI infrastructure, distributed microservices, real-time data pipelines, and agentic AI systems. Defines technical strategy, builds secure and observable production services, processes high-volume network data, and mentors engineers. The role requires hands-on software engineering leadership across the full lifecycle, including design, coding, testing, cloud deployment, operations, and technical reviews.

Lead the architecture and development of scalable AI infrastructure, distributed microservices, real-time data pipelines, and agentic AI systems for intelligent networking. Drive the full software lifecycle from design through production operations, establish technical direction, mentor engineers, and improve system reliability, security, observability, performance, and scalability.

Lead the architecture and development of scalable AI infrastructure, distributed microservices, real-time data pipelines, and agentic systems for intelligent networking. Drive the full software lifecycle, establish technical direction, mentor engineers, and ensure production systems are secure, observable, resilient, and highly performant.

Lead the technical vision, architecture, development, testing, deployment, and operations of scalable AI infrastructure, distributed microservices, real-time data platforms, and agentic AI systems. Build secure, resilient, observable services processing high-volume network data; guide technical strategy, improve engineering practices, and mentor engineers. Translate complex technical challenges into production-ready solutions across intelligent networking, cloud platforms, analytics, and automation.

Leads the architecture, development, deployment, and operation of scalable AI infrastructure, distributed microservices, real-time data pipelines, and agentic systems for intelligent networking. Drives technical vision, builds secure and observable production services, mentors engineers, leads technical discussions, and improves system reliability and performance. Requires extensive software engineering and distributed systems experience, proficiency in a general-purpose programming language, cloud expertise, and familiarity with AI, stream processing, network telemetry, or large-scale analytics.

Lead the architecture, development, testing, deployment, and operation of scalable AI infrastructure, distributed microservices, real-time data platforms, and agentic AI systems. Define technical vision, build secure and observable high-performance services, process large-scale network data, and integrate intelligent networking capabilities. Mentor engineers, lead technical discussions and reviews, improve system reliability and performance, and translate complex technical challenges into production-ready solutions.

Lead the architecture and development of scalable, secure, observable AI infrastructure, distributed microservices, real-time data pipelines, and agentic systems for intelligent networking. Drive technical vision, software delivery, system reliability, and operational excellence while mentoring engineers. Build production platforms processing high-volume network and operational data, integrating cloud infrastructure, machine learning, telemetry, and automation capabilities.

Lead the architecture, development, testing, deployment, and operation of scalable AI infrastructure, distributed microservices, real-time data pipelines, and agentic AI systems. Define technical vision, build secure and observable production services, process high-volume network data, mentor engineers, and guide technical strategy across intelligent networking and cloud-native platforms.

Design, implement, operate, and maintain multi-cloud platforms across GCP, AWS, and Azure. Provide 24/7 cloud operations, troubleshooting, monitoring, security, compliance, backup, high availability, disaster recovery, and outage analysis. Automate infrastructure and deployment processes using Terraform, GitHub, scripting, and CI/CD practices. Support incident management, service requests, documentation, cloud workload migrations, and continuous improvement within ITIL-based operations.

Build and operate automated compute-capacity systems across regions, including forecasting, provisioning, reservations, fleet reconciliation, drift detection, observability, alerting, and cost optimization. Support demand planning for customer commitments, migrations, and new regions. Contribute to right-sizing, autoscaling, workload consolidation, capacity incident response, and post-incident improvements while coordinating with engineering and finance stakeholders.

Administers and architects IBM i environments across IBM Power Systems, managing partitions, upgrades, backups, disaster recovery, high availability, security, performance, storage, and integrations. Develops automation with CL, SQL, and RPG; supports IBM MQ, APIs, cloud platforms, and open-source technologies. Serves as the highest technical escalation point, leads root-cause analysis, participates in on-call support, and manages infrastructure changes, modernization initiatives, documentation, and compliance.

Develop and support security automation solutions across Cortex XSOAR and Splunk. Build integrations, automated workflows, playbooks, and security data-source pipelines in collaboration with Incident Response, Threat Intelligence, Insider Risk, and SOC teams. Maintain scalable internal and third-party tools, improve SOC efficiency, and support security monitoring and incident investigation. The role requires strong Python software development, Linux, web technologies, Git, SQL, and cybersecurity operations knowledge.

Develop and support cybersecurity automation across Cortex XSOAR and Splunk. Build integrations, automated workflows, playbooks, and security data-source onboarding processes while improving SOC efficiency, reliability, and scalability. Collaborate with Incident Response, Threat Intelligence, Insider Risk, and SOC teams. Maintain internal and third-party tools, manage competing requests, and develop software using Python, web frameworks, Linux, Git, SQL, and front-end technologies.

Own the organization’s Zoho environment as its sole developer. Build and release Zoho Creator applications, customize Zoho business applications, and develop automations and integrations using Deluge, APIs, OAuth, webhooks, and scheduled jobs. Translate department requirements into specifications, then handle design, testing, deployment, training, documentation, data migration, security, and maintenance. The role is strictly on-site in New Delhi and requires strong independent judgment, production Zoho development experience, and integration expertise.

Designs, develops, integrates, tests, and maintains production embedded Linux software for vehicle systems. Responsibilities include modern C/C++ and Qt/QML development, Yocto platform maintenance, Python automation, CI/CD, automated testing, debugging across hardware and software boundaries, release management, architecture, documentation, and production support. The role also provides technical leadership and mentorship while collaborating with multidisciplinary engineering, manufacturing, cybersecurity, and supplier teams.

Build and experiment with LLM prompting, retrieval architectures, multilingual conversational interfaces, RAG pipelines, and chatbot or agentic AI prototypes. Improve NLP dataset readiness through schema alignment and metadata tagging, and develop evaluation modules addressing hallucination, bias, safety, and privacy across multilingual and domain-specific contexts. Collaborate with the Responsible AI team across projects while supporting applied research and communicating progress independently.

Lead data strategy and governance across civic technology initiatives while managing multidisciplinary data teams. Oversee data and AI product development, feature prioritization, analytics, visualization, documentation, compliance, and quality. Collaborate with product, technology, and sector teams to deliver user-centered solutions, support open-source projects, engage stakeholders, conduct field pilots, and contribute to fundraising and thought leadership. The role is based in Delhi and requires travel for implementation, training, and stakeholder engagement.

Conduct penetration tests and vulnerability assessments across applications, networks, APIs, cloud environments, and infrastructure. Analyze scan results, identify and prioritize weaknesses, document risk ratings, communicate findings to technical and non-technical stakeholders, recommend remediation, coordinate remediation activities, and maintain vulnerability, asset, and configuration databases.