Top Python Jobs in Bangalore

Design, build, and own core backend infrastructure and microservices that support ML, frontend, and platform teams. Implement distributed config, rate limiting, feature flags, A/B testing, and traffic capture/replay. Improve performance, scalability, and observability of cloud infrastructure; deliver deadline-sensitive, interdependent work and influence the infrastructure roadmap.

Design, build, and operate platforms and backend systems at Rubrik. Own Kubernetes, develop distributed services, and collaborate with engineering teams.

Lead full-stack engineering across distributed microservices: design, develop, test, deploy and support solutions. Drive serverless and container initiatives, improve build/deployment pipelines, mentor engineers, debug cross-stack issues, and lead strategic technical projects.

Lead technical architecture and end-to-end design for real-time, high-availability software systems. Select technologies, enforce SDLC standards, mentor engineers, define CI/CD and observability, address technical debt, collaborate with stakeholders, and produce technical documentation.

Leads the design, development, troubleshooting, and delivery of high-performance software for fiber-based OLT platforms. Works with GPON/XGPON, Layer 2 forwarding, multicast, QoS, VLANs, network processors, and packet processing. Collaborates with product management, translates customer needs into features, drives technical execution across the SDLC, and mentors engineering teams. Contributes to software testing automation and agile development practices.

Build and maintain scalable cloud-native data platforms, APIs, SDKs, and microservices supporting global procurement and financial transaction flows. Develop AI and machine learning solutions, ensure data quality and observability, apply infrastructure-as-code and DevOps practices, troubleshoot production issues, and collaborate with engineers, architects, and business teams using Agile methodologies.

Monitor and support a multi-cloud infrastructure across Azure and AWS, including Windows, Linux, and SQL Server systems. Responsibilities include incident response, alert triage, patching, compliance tracking, network troubleshooting, reliability reporting, runbook improvement, and automation. The role participates in a follow-the-sun on-call rotation and supports VPNs, DNS, subnets, routing, monitoring tools, and infrastructure maintenance.

Leads cloud platform architecture, reliability, modernization, automation, cost optimization, and operational excellence across Azure-based SaaS infrastructure with some AWS. Manages and develops cloud and database engineers, establishes observability and incident-response practices, improves CI/CD, supports highly available systems, and partners with engineering, product, and security teams. The role remains hands-on with Infrastructure-as-Code while overseeing hiring, performance management, capacity planning, and technical strategy.

Owns and modernizes Litmos’s Microsoft Azure environment, including infrastructure, networking, governance, security, cost optimization, and cloud-native migrations. Administers SQL Server and supports PostgreSQL, Synapse, and Azure AI Foundry platforms. Builds Infrastructure as Code with Bicep, automates operations using PowerShell and Python, improves CI/CD, strengthens observability and disaster recovery, and supports GDPR compliance across a distributed US/Australia team.

Leads a remote engineering team building scalable Python and Golang microservices for Canonical’s software distribution marketplaces. Responsibilities include mentoring and developing engineers, managing delivery and expectations, shaping technical strategy and roadmaps, reviewing code, guiding architecture, maintaining engineering quality, and collaborating with product managers, architects, other teams, open-source contributors, and commercial partners.

Leads the design, development, and maintenance of scalable cloud-native data platforms, APIs, SDKs, and microservices. Architects distributed solutions using AWS, containers, infrastructure as code, and data pipelines while ensuring quality, observability, security, and reliability. Provides technical mentorship, leads design discussions and code reviews, resolves production issues, and develops AI/ML solutions. Collaborates with architects, product managers, business stakeholders, and globally distributed engineering teams using Agile and DevOps practices.

Lead development of scalable cloud-native applications, microservices, RESTful APIs, data platforms, and CI/CD pipelines across AWS environments. Provide architectural leadership, technical strategy, code reviews, performance optimization, testing, observability, production troubleshooting, and mentorship. Build responsive React interfaces, backend services using Node.js, Python, or Java, NoSQL data stores, and AI/ML solutions while collaborating with product and engineering teams.

Deliver, operate, and improve Microsoft Azure platform services through cloud engineering, automation, Infrastructure as Code, and operational support. Responsibilities include Azure administration, monitoring, security, incident resolution, networking, platform reliability, PowerShell and Python automation, CI/CD support, project delivery, service transition, and continuous improvement. The role collaborates with architects, stakeholders, vendors, and technical teams to provide secure, resilient, standardized, and cost-effective cloud services.

Design, develop, test, and maintain full-stack React applications and Node.js services using scalable cloud-native architectures. Build RESTful APIs, microservices, databases, and CI/CD pipelines while optimizing performance, reliability, security, and cost. Collaborate with product and engineering teams, review code, troubleshoot distributed systems, document solutions, and provide technical leadership and mentorship. Integrate enterprise and supply-chain systems while contributing to architecture evolution and AI-driven engineering improvements.

Leads the design, development, testing, and maintenance of scalable full-stack applications using Python and Angular or React. Builds REST APIs, microservices, databases, and responsive interfaces; manages Docker, Kubernetes, Terraform, cloud infrastructure, and CI/CD automation. Troubleshoots production issues, improves reliability and performance, participates in architecture and code reviews, and ensures secure, scalable coding practices.

Build and manage CI/CD pipelines for AI, machine learning, and generative AI initiatives in cloud environments. Automate monitoring, troubleshooting, and maintenance of cloud infrastructure. Collaborate with architects to design deployment modules that optimize infrastructure performance and cost.

Designs, develops, tests, deploys, and supports secure Salesforce solutions using Apex, LWC, Flow, integrations, AWS serverless services, Python, and generative AI frameworks. Translates business requirements into scalable technical solutions, develops features across Salesforce clouds, manages full delivery lifecycles, performs root-cause analysis, and mentors engineers. The role also leads project delivery, estimates effort, documents solutions, and builds automation, conversational workflows, copilots, and AI agents.

The Engineering Manager will lead the architecture and development of scalable software systems, ensuring code quality and resource allocation, while collaborating with teams on technical execution and best practices.

The Product Support Engineer III role involves leading investigations of mobile issues, collaborating with teams, mentoring engineers, and improving product quality. This senior position requires strong troubleshooting and communication skills, with a focus on customer impact and technical depth.

Leads technical delivery for IBM i and Power Systems managed services and projects. Responsibilities include security, performance optimization, patch and PTF management, upgrades, migrations, automation, high availability, disaster recovery, infrastructure architecture, and client advisory work. The role also supports modernization, managed services, pre-sales solutioning, vendor coordination, and client-facing execution planning.

Build and deploy production communications and AI solutions for enterprise customers in India. Responsibilities include technical discovery, architecture, proof-of-concepts, production launches, LLM gateway deployment, model routing, observability, APIs, Kubernetes services, and high-concurrency event-driven systems. The role owns customer outcomes, troubleshoots complex integrations, creates documentation, leads technical discussions, and collaborates with Product and Engineering. It requires customer-facing engineering, travel across India, and expertise in cloud-native software, AI workloads, and real-time communications.

Lead full‑stack development across frontend and backend, design and operate scalable SaaS systems, embed AI capabilities, modernize legacy services, build RESTful APIs and microservices, review code, and collaborate with product and design to deliver high‑quality user experiences.

Leads systems engineering for middleware and distributed platforms, including OpenShift and Kubernetes deployments, CI/CD automation, cloud infrastructure, application onboarding, SSL certificate lifecycle management, security patching, performance monitoring, troubleshooting, and platform integration. Collaborates across teams to resolve technical issues, improve system reliability, and ensure applications meet performance and security standards.

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.

Develop and correlate architectural power estimation models and tools for NVIDIA GPUs and SoCs. Estimate chip, board, idle, and I/O power across product use cases; calibrate models against silicon measurements; evaluate chip configurations and process technologies; and improve performance-per-watt. Collaborate with architecture, design, synthesis, timing, circuit, laboratory, and post-silicon teams.