Top Python Jobs in Kolkata

As a Senior Solution Integrator, you will lead integration and deployment of Ericsson Charging solutions, ensuring high-quality implementations and efficient collaboration with teams to meet customer requirements.

Deploy, configure, integrate, develop, and troubleshoot telecom mediation platforms across bare metal, virtualized, cloud, and container environments. Build mediation workflows for high-volume CDR processing, integrate with network and billing systems, develop automation and streaming apps (Kafka/Flink), perform data reconciliation, and leverage Gen-AI and scripting for productivity and solution development.

Deploys, configures, integrates, migrates, and tests IT and telecom cloud platforms for Ericsson and third-party solutions. Develops Python and Shell automation, supports presales solution analysis, evaluates deployment feasibility and impacts, and executes User Acceptance Testing. Requires Linux administration, cloud and virtualization expertise, troubleshooting, technical communication, and collaboration across international project teams.

Design and deliver end-to-end packet core and 5G core solutions, optimize network performance, collaborate with product, R&D and customer teams, lead transformations, perform protocol and data analysis, and support deployment and knowledge transfer.

Develops and integrates radiating components and passive radiation-pattern structures for multiband base-station antennas. Responsibilities include 3D and 2D electromagnetic simulation, prototype RF measurements, performance optimization, troubleshooting, technical documentation, and supporting the product lifecycle through mass production. The role collaborates with international cross-functional teams and requires relocation to Rosenheim, Germany.

Design, deploy, and manage scalable Google Cloud infrastructure, Kubernetes workloads, serverless applications, and Azure DevOps CI/CD pipelines. Use Terraform and scripting to automate provisioning, deployments, scaling, monitoring, cost optimization, and zero-downtime releases. Implement GCP networking, storage, load balancing, security, IAM, compliance, and DevSecOps practices across cloud environments.

Review and integrate application and technical architecture requirements across security, integration, performance, quality, and operations. Design and implement Databricks data ingestion and end-to-end pipelines from multiple sources using cloud platforms, ETL, data engineering, and programming languages such as Python, PySpark, or Scala. Lead solution workshops, support RFP pursuits, engage clients, and coordinate multiple stakeholders while delivering data-driven technical solutions.

Designs, builds, automates, monitors, and optimizes Snowflake-based AI/ML infrastructure. Manages warehouses, databases, secure access, Snowpark workloads, Streamlit applications, data and feature pipelines, integrations, CI/CD, infrastructure-as-code, observability, governance, security, and cost optimization. Collaborates with data scientists, ML engineers, data engineers, platform engineers, and architects to deploy reliable enterprise AI solutions.

The Systems Administrator manages IT infrastructure, oversees server and network performance, automates deployments, ensures security, and documents processes while supporting IT operations.

Administer and support Kubernetes platforms across GKE and AKS, including monitoring, incident response, troubleshooting, reliability improvement, GitOps deployments, CI/CD, Terraform automation, and operational documentation. The role manages production incidents, leads root-cause analysis and post-incident reviews, collaborates with cloud and application teams, and participates in 24/7 on-call rotations.

Build and support standalone web applications, internal tools, integrations, and workflow automations end to end. Responsibilities include application design, frontend and backend development, database integration, API development, Azure deployment, CI/CD, access control, monitoring, and production support. The role also involves scoping ambiguous stakeholder needs into shippable solutions and using agentic coding tools such as Claude Code or Codex.

Architects, validates, and documents enterprise solutions built on S3-compatible object storage. Designs reference architectures and integration, interoperability, scalability, and performance tests across data protection, analytics, AI/ML, search, and data lake platforms. Troubleshoots distributed environments, analyzes telemetry, leads root-cause investigations, and supports customer and partner escalations. Produces technical documentation, benchmarks, sizing guidance, whitepapers, and presentations for engineering, partners, customers, sales teams, and executives.

Designs and maintains end-to-end business process automations spanning browser/RPA tools, workflow platforms, backend services, APIs, databases, internal dashboards, and AI-agent workflows. The role develops reliable integrations, applies RAG and vector search, deploys containerized solutions through CI/CD, troubleshoots failures, documents architectures, and identifies manual processes suitable for deterministic or AI-driven automation. Collaboration with product, engineering, and business stakeholders is required.

Develop and deploy scalable cloud-native enterprise applications, APIs, microservices, event-driven architectures, and AI-enabled solutions. Build RAG applications, intelligent agents, automated testing frameworks, CI/CD pipelines, and infrastructure automation. Troubleshoot production issues, contribute to architecture and security standards, modernize platforms, identify AI opportunities, and mentor engineers. The role requires strong Microsoft-stack, cloud, DevOps, software architecture, and AI development expertise.

Develop scalable, high-performance backend applications using Python. Responsibilities include Core Python and object-oriented programming, functional programming, multithreading, multiprocessing, asynchronous development, REST API creation and integration, SQL query optimization, Apache Spark distributed processing, debugging, performance tuning, and problem-solving.

Manage Azure administration and DevOps infrastructure, including CI/CD pipelines, infrastructure as code, containers, Kubernetes, and microservice deployments. Deploy and scale AI and ETL workloads using Azure services, Python, and PySpark. Implement DevSecOps, secrets management, RBAC, monitoring, logging, governance, and Git-based collaboration while supporting Agile development practices.

Own AWS infrastructure through Terraform and build GitHub Actions CI/CD pipelines for Django, Python, Node.js, and React services. Manage production deployments, migrations, observability, incident response, PostgreSQL, Redis, messaging systems, security hardening, and reliability improvements. Develop Python and shell automation, maintain runbooks, and provide detailed shift handovers. The role requires production ownership, on-call participation, autonomy, and either normal or night-shift availability.

Develop and maintain IoT applications, firmware, and connected-device solutions for microcontrollers, sensors, and edge devices. Integrate devices with cloud and backend systems using communication protocols, build APIs and data services, troubleshoot connectivity and performance, and apply IoT security practices. Collaborate across hardware, software, and product teams while contributing to testing, code reviews, documentation, deployment, and quality assurance.

Develop reusable, scalable, and testable Python applications using Django or Flask. Analyze requirements, build REST APIs, integrate external services and multiple databases, connect frontend elements with server-side logic, and implement authentication, authorization, security, and data protection. Experience with PostgreSQL, MySQL, NoSQL databases, and familiarity with JavaScript or Angular are relevant.

Lead technical direction and architecture for a cloud-native SaaS platform. Design scalable distributed systems, drive platform modernization, mentor engineers, deliver high-performance backend services, improve observability and reliability, and apply AI-enabled engineering to boost productivity and quality.

Architect and develop block-level verification environments using SystemVerilog and UVM; create constrained-random verification suites; run front-end simulations (VCS/NC), analyze code and functional coverage, perform gate-level signoff, debug ASIC logic with designers, and write scripts (Perl/Python/Tcl/shell) to improve verification infrastructure.

Build, test, and maintain backend and/or frontend features for a cloud-native SaaS platform. Develop and consume REST APIs, write well-tested maintainable code, participate in design and code reviews, troubleshoot production issues, and collaborate with product, design, and QA. Learn and apply AI-assisted development and cloud-native practices.

Design, build, and own end-to-end cloud-native SaaS features and services. Implement scalable APIs, event-driven workflows, background workers, and async processing. Improve performance, reliability, and observability; participate in design reviews, on-call rotation, mentoring, and cross-team collaboration. Apply AI-assisted development practices while maintaining security and quality.

Lead architecture and technical direction for cloud-native, high-scale SaaS platforms. Design distributed systems, drive platform modernization, mentor engineers, implement scalable APIs and backend services on AWS, and improve reliability, performance, observability, and DevOps practices.

Design, build, and maintain backend APIs and services for a real-time supply chain visibility platform. Own system architecture, real-time event ingestion, data normalization, ML integration, monitoring, and production debugging while collaborating with Product and Data Science to deliver scalable, high-availability features.