Top Python Jobs in Bengaluru

Owns product features end to end across backend, frontend, mobile, infrastructure, and production operations. Builds AI agents and automated healthcare workflows, designs services and APIs, manages infrastructure, writes model evaluations, monitors production systems, and handles incidents. The role requires strong Python and TypeScript full-stack skills, hands-on AI harness experience, daily use of coding agents, product judgment, and the ability to independently take ambiguous problems from concept to deployment.

Build and own full-stack healthcare platform features from concept through production. Responsibilities include developing AI agents and automated workflows, web and mobile experiences, APIs, data models, infrastructure as code, monitoring, incident response, model evaluations, and secure PHI handling. The role requires strong Python and TypeScript skills, hands-on AI harness experience, daily use of coding agents, product judgment, and end-to-end ownership in a distributed engineering team.

Build and scale high-performance backend services for a real-time threat intelligence platform. Develop low-latency streaming architectures, optimize OpenSearch or Elasticsearch indexing, manage AWS/EKS deployments, and translate broad goals into technical specifications and maintainable code. Collaborate with teammates to identify architectural gaps and improve systems. The role requires production backend experience with Python or Golang, Kafka or Kinesis, search platforms, Kubernetes, AWS, and PostgreSQL.

Develops and maintains Python software solutions for digital pathology systems. Responsibilities include evaluating requirements, designing and installing software, conducting systems analysis, documenting solutions, improving operational processes, troubleshooting development and service issues, and following the software development lifecycle. The role requires experience with interactive applications, MongoDB and other non-relational databases, test-driven development, software engineering tools, and requirements documentation.

Leads DevOps, SRE, DevSecOps, and platform reliability across Azure and AWS. Owns Kubernetes infrastructure, CI/CD, GitOps, databases, observability, security, distributed systems, incident response, disaster recovery, and FinOps. Builds and mentors engineering teams while improving availability, deployment safety, MTTR, DORA metrics, compliance, and cloud cost efficiency. This hands-on leadership role requires deep cloud-native, infrastructure, automation, and production troubleshooting expertise.

Build and operate secure, reliable cloud-native deployments for a healthcare SaaS platform. Own CI/CD pipelines, GitOps workflows, Kubernetes deployments, Azure infrastructure, infrastructure-as-code, observability, database operations, security automation, and cloud cost optimization. Troubleshoot production systems, participate in on-call rotations, improve deployment and recovery processes, and reduce operational toil through automation.

Own the architecture and technical direction of regulatory data systems, including safety data sheet generation, rule engines, substance data, and regulatory integrations. Build scalable backend services with Node.js, TypeScript, and AWS, develop agentic data workflows, lead technical specifications and architectural decisions, manage regulatory scoping and execution, establish engineering standards, and mentor senior engineers.

Own end-to-end quality for web platforms and mobile apps by writing test cases, building automated regression suites, evaluating AI-powered testing tools, validating data and user journeys, and supporting releases. The role includes bug reporting, production investigation, customer-facing technical support, documentation, and collaboration with engineers to verify fixes. The engineer will work with Playwright, Cypress, Selenium, and AI tools while developing broader engineering skills.

Own the architecture, reliability, freshness, quality, and cost of CertifyOS’s data platform. Lead engineers delivering distributed batch and real-time pipelines, OLTP, OLAP, and NoSQL systems; drive entity resolution and master data management; build data products and ML foundations; improve scale and performance; establish observability and SLAs; mentor engineers; and participate in on-call incident response.

Build AI-assisted quality engineering workflows, scalable UI/API/integration and end-to-end automation, performance and load tests, and reliability checks. Integrate automated testing into CI/CD pipelines, establish quality gates, analyze failures and bottlenecks, and validate distributed systems, databases, asynchronous workflows, and recovery behavior. Collaborate with engineering and product teams to improve test coverage, scalability, release confidence, and development productivity.

Provide L2 technical support for Pramana's products, manage escalations, ensure compliance, and deliver high-quality customer service, including emergency on-call coverage.

Leads formal verification for complex semiconductor and silicon designs, including verification planning, assertions, properties, checkers, protocol analysis, bug triage, and closure. Collaborates with architects, RTL designers, and validation teams; improves reusable verification flows and automation; mentors engineers; and supports effort estimation, progress tracking, and risk management.

Leads firmware and PCIe switch QA activities, including functional, performance, interoperability, stress, signal-integrity, protocol, compliance, PRBS, loopback, and margining tests. Develops manual and automated testing using Python, analyzes PCIe traces, triages and debugs issues with firmware and silicon teams, manages requirements and traceability, coordinates schedules and dependencies, communicates with hyperscalers and OEMs, and mentors team members.

As a Forward Deployed Engineer, you will design, build, and deploy AI agents, integrating them with external systems, optimizing performance, and advising customers on AI architecture and scalability.

Lead the architecture and evolution of Albert OS data platforms, including lakehouse infrastructure, analytical pipelines, transactional systems, and batch and streaming ingestion. Define data modeling standards, optimize SQL and NoSQL performance, establish data security and observability practices, and collaborate with API and Data Science teams on shared data contracts. Mentor engineers and guide cross-functional architectural decisions.

Architects and operates scalable cloud and on-premise infrastructure, CI/CD pipelines, Kubernetes platforms, and infrastructure-as-code workflows. The role focuses on automation, system availability, security, performance, incident response, troubleshooting, monitoring, and operational efficiency. The engineer collaborates across engineering, security, and product teams, prototypes emerging technologies, supports production systems, and drives root-cause analysis and continuous improvement.

Build and manage observability solutions using Datadog and Splunk across applications, cloud infrastructure, APIs, and Kubernetes. Develop dashboards, alerts, reports, SPL queries, and distributed tracing capabilities. Troubleshoot production incidents, conduct root cause analysis, and improve system reliability in collaboration with DevOps, SRE, application, and infrastructure teams. Automate monitoring tasks using Python, Bash, and Terraform.

Administer and automate Linux-based cloud infrastructure across Azure and/or GCP. Responsibilities include provisioning resources, managing Kubernetes, maintaining CI/CD pipelines, writing infrastructure as code and Bash automation, monitoring systems, troubleshooting production issues, supporting security compliance, and documenting operational procedures. The role requires an active Azure or GCP certification matching hands-on experience and at least three weekly days in the Bangalore office.

The Software Engineer will participate in software engineering tasks, collaborate on core systems, and support customer development projects in a startup environment.

Build, deploy, test, and maintain CI/CD processes using Jenkins, Maven, and Git. Automate testing and deployments, monitor applications, select technologies aligned with business needs, and collaborate with development and operations teams to meet performance expectations. Manage multiple servers, databases including MongoDB, Redis, and Elasticsearch, containerized applications with Docker and Kubernetes, and Node.js and Python web servers. Blue-green deployment experience is advantageous.

Design, develop, maintain, troubleshoot, and upgrade software applications. Collaborate with cross-functional teams to deliver new features, write clean and scalable code, participate in code reviews, share knowledge, and stay current with software development trends and technologies.

Maintain client relationships and technical support throughout the build, deployment, and ongoing lifecycle. Administer Linux systems, Kubernetes, Docker, AWS environments, CI/CD pipelines, and distributed applications. Troubleshoot Java servers, Nginx, APIs, storage, and infrastructure incidents. Create technical documentation, manage tickets, resolve problems promptly, and collaborate with teams while adapting to evolving technologies.

Build and lead development of Suki’s real-time clinical AI platform, including backend services, audio streaming, LLM orchestration, AI agents, APIs, SDKs, and distributed infrastructure. Deploy and operate scalable systems on Kubernetes and GCP while meeting HIPAA and SOC 2 standards. Lead design reviews, mentor engineers, improve AI-native development practices, and contribute to critical code and incidents.

Own and scale high-throughput backend systems powering real-time voice AI, LLM features, platform services, and data systems. Design production services in Go or Python, optimize Kubernetes workloads and cloud costs, manage distributed systems and databases, establish observability and reliability practices, mentor engineers, and support enterprise customer requirements.

Build and operate secure, scalable backend services and data ingestion pipelines. Own features from design through production, develop third-party API integrations, improve data freshness and reliability, troubleshoot distributed systems, and participate in on-call support. Collaborate across engineering and product teams while using monitoring, testing, and documentation to maintain production quality.