Top Python Developer Jobs in Delhi

Monitor, triage, and investigate cybersecurity alerts across SIEM, EDR, cloud, endpoint, network, and enterprise environments. Analyze logs, investigate suspicious activity, support incident response and remediation, coordinate escalations, improve detection quality, tune whitelists, and prepare technical reports. Maintain SOC documentation and contribute to operational improvements within a global 24/7 security operations centre.

Build and ship AI-powered features for fashion, beauty, and home using large-scale product, image, and consumer data. Prototype with LLMs, agents, multimodal and CV models, run experiments, measure impact, and take models end-to-end from hypothesis to production while collaborating with product, design, and business teams.

Provides third-tier support for Red Hat Identity Management services across on-premises and cloud environments. Responsibilities include resolving complex incidents, maintaining and monitoring IAM components, configuring users, groups, hosts, policies, and Linux services, supporting upgrades, taking proactive action on alerts, and mentoring junior staff. The role interfaces with T2 support, service delivery, and technical subject matter experts.

Lead end-to-end ML systems: data pipelines, model development (transformer-based detection), sim-to-real synthetic data, multi-sensor fusion, on-device real-time inference (Jetson), MLOps (experiment tracking, versioning), and production deployment and monitoring. Set ML roadmap and hire/lead as the team grows.

Supports and implements Planful FP&A and consolidation modules, including workflow modeling, automation, technical design, testing, documentation, maintenance, reporting, user access, training, and business-as-usual support. Collaborates with stakeholders to improve financial planning processes, troubleshoot issues, and maintain a positive user support experience. The role also applies analytical, problem-solving, and basic project management skills while working with ERP and automation tools.

Lead the technical roadmap, architecture, development, evaluation, and productionization of machine learning and AI solutions for search relevance. Build models using queries, product catalogs, and behavioral data; integrate scalable ML components into cloud systems; analyze search quality; mentor engineers; and influence cross-functional engineering and product decisions.

Build and support fund accounting data solutions for asset management, including integrations, transformations, reconciliations, controls, and finance reporting products. Develop large-scale data pipelines using Databricks, Python, PySpark, and SQL; work with investment data, NAV calculations, accruals, corporate actions, fees, and general ledger information. Support cloud-based delivery, data quality, orchestration, CI/CD, and direct collaboration with US stakeholders.

Build and maintain JavaScript and React applications, cloud infrastructure, AI-enabled workflows, scalable APIs, event-driven systems, and healthcare integrations. The role involves working with telephony platforms, AI providers, and third-party services while advancing autonomous workflow orchestration. Engineers will use modern AI-assisted development tools, contribute independently in a startup environment, and collaborate during consistent EST hours.

Operate and improve production data infrastructure across large-scale distributed cloud systems. Monitor performance, manage alerts, respond to incidents, perform root cause analysis, automate repetitive tasks, support CI/CD pipelines, document runbooks, and assist with capacity planning. The role requires participation in an on-call rotation and collaboration with Engineering to maintain reliability, efficiency, and uptime.

Performs manual white-box penetration testing, application security assessments, vulnerability hunting, and code reviews across Atlassian software, platforms, and services. Partners with security, engineering, and infrastructure teams to validate technical controls and strengthen security. The role requires understanding web application and cloud security, coding in Java, Python, or Go, leading projects, mentoring practitioners, and communicating with technical teams.

Develops, tests, configures, and supports Connected Factories and Industrial IoT applications across global manufacturing sites. Responsibilities include troubleshooting, deployment, system validation, data-quality checks, performance monitoring, secure coding, issue resolution, stakeholder collaboration, documentation, and user training. The role requires expertise in Ignition 8.1, SQL, Python, manufacturing connectivity protocols, IT networks, and digital manufacturing environments.

Own optical architecture, integration, validation, design verification testing, manufacturing handoff, and product release for coherent transceivers and transponder line cards. Lead cross-functional closure of optical performance issues across optics, DSP, firmware, ASIC, PIC, mechanical, thermal, and hardware teams. Define oDVT coverage, calibration and manufacturing test strategies, automation, documentation, and release approvals while ensuring compliance with product requirements and industry standards.

Leads design verification for radar IP, subsystems, and SoCs from specification through post-silicon validation. Owns verification strategy, methodology, environments, coverage, regressions, traceability, and signoff across multiple programs. Builds and mentors verification teams, collaborates with architecture, RTL, physical design, firmware, systems, and applications teams, and supports customer reviews and ISO 26262/ISO 21434 certifications. The role requires expertise in SystemVerilog/UVM, C-based verification, digital design, protocols, formal verification, and post-silicon debugging.

Build, validate, and release software for ARM-based platforms. Develop Python and Shell automation, improve CI/CD pipelines, troubleshoot Linux and architecture-specific failures, and investigate root causes using debugging and system tools. Collaborate with distributed engineering teams on build systems, cross-compilation, security controls, REST APIs, microservices, and database testing.

Owns the design, development, delivery, and lifecycle management of scalable cloud-native applications. Leads distributed systems, microservices, platform architecture, CI/CD, Kubernetes deployments, observability, test automation, reliability engineering, and DevSecOps practices. Provides technical leadership and mentorship while collaborating with cross-functional teams. Uses Java, Python, automation frameworks, cloud-native platforms, and AI-assisted development tools to improve software quality, delivery speed, and operational efficiency.

Develop and deploy production machine learning systems for fall detection and health risk scoring. Build classical ML models, engineer features from radar and point-cloud data, contribute to pose estimation, and create Databricks training and inference pipelines. Own model evaluation and false-alarm reduction for a safety-critical system, monitor deployed models, and mentor team members while working in a fast-moving environment.

Design, deploy, and operate production-scale data platforms in secure, fully air-gapped customer environments. Translate client requirements into working solutions, independently own implementation and delivery, troubleshoot manual deployments, collaborate with technical and non-technical stakeholders, travel to client sites, and mentor junior engineers.

Designs, implements, and maintains scalable, secure, reliable cloud infrastructure using AWS, Terraform, AWS CDK, and CI/CD automation. The role involves cloud architecture, networking, security, high availability, cost optimization, troubleshooting, and infrastructure-as-code development. It also requires collaboration, technical solution design, root-cause analysis, and ownership of maintainable infrastructure solutions.

Design and develop secure, scalable Python backend systems; contribute to architecture, APIs, microservices, databases, and performance optimization. Conduct code reviews, troubleshoot and maintain systems, establish testing and coding standards, and mentor junior engineers. Collaborate cross-functionally to deliver high-quality applications while driving continuous improvement and engineering best practices.

Build and maintain ETL pipelines, data transformations, data models, BI dashboards, and reports. Design scalable relational database schemas and use Python or Java, SQL, AWS, and workflow orchestration to solve complex production data problems. Translate technical findings into business insights while collaborating with technical and non-technical stakeholders. Apply Agile practices and support enterprise and SaaS release cycles, with healthcare compliance experience preferred.

Owns test automation, continuous integration, regression, test environments, pipelines, and release verification for a cloud-native telecommunications network management platform. Performs feature, system, deployment, upgrade, security, and release testing using Robot Framework, Python, Bash, Docker, Kubernetes, and CI/CD tools. Uses AI-assisted development tools and coaches junior engineers on test reliability and automation best practices.

Partner with Account Executives to win enterprise deals in India by leading technical discovery, solution design, product demonstrations, workshops, proof-of-value engagements, and technical evaluations. Build relationships with engineering leaders, architects, and DevOps teams; translate complex technology into business outcomes; support customer champions; and provide field feedback to Product and Engineering. The role requires expertise in enterprise SaaS, DevOps, CI/CD, feature management, progressive delivery, and modern software architectures.

Build and maintain cloud data pipelines, transformations, orchestration workflows, governance controls, and analytics-ready datasets. Integrate APIs, Databricks, BI tools, and platform connectors while troubleshooting data quality and performance issues. Collaborate with product, engineering, DevOps, security, and client-facing teams on architecture, access management, infrastructure migrations, documentation, and production support.

Build and manage production AI agents, high-precision RAG pipelines, and LLM-powered features. Develop backend architecture using Postgres, REST APIs, asynchronous programming, queues, storage, RBAC, and encryption. Integrate foundation models, establish evaluation patterns, write automated tests, monitor system health, and collaborate with product managers on reliable, secure AI applications.

Develop scalable backend services and APIs, create coding tasks and deterministic verifiers for AI systems, debug complex codebases, optimize performance, refactor legacy systems, implement features, and provide technical reviews and reasoning. The role is remote, contract-based, and part-time at 15–20 hours per week.