Top Engineering Jobs

Lead the architecture and modernization of C#/.NET test automation for Kubernetes-based distributed applications. Design reusable test libraries, API and integration testing, CI/CD quality gates, diagnostics, and resilience validation. Investigate complex failures using logs, metrics, traces, and Kubernetes evidence. Establish risk-based testing strategies, reduce flaky tests, improve execution efficiency, influence product testability, and mentor engineering teams across the organization.

Own the technical development and evolution of Salesforce CPQ and quote-to-cash systems. Build Apex, Flow, and Lightning Web Components; configure pricing, approvals, and quoting workflows; and maintain Salesforce-NetSuite integrations using Workato. Lead CI/CD, DevOps, testing, deployments, troubleshooting, and release management. Partner with Revenue Operations, Finance, Deal Desk, and Sales to deliver scalable solutions, mentor developers, and advance AI-enabled revenue automation.

Architects and operates CI/CD platforms, Jenkins agent infrastructure, GitHub governance, and VMware virtualized environments. Owns infrastructure lifecycle from hardware and operating systems through networking, monitoring, and troubleshooting. Builds infrastructure-as-code with Terraform, Ansible, and Packer; advances Kubernetes and Docker strategies; establishes observability and reliability standards; and supports release engineering. Acts as a technical escalation point across infrastructure and pipeline layers, drives platform strategy, introduces AI-assisted automation, and mentors engineers.

Develop and scale C#/.NET test automation for DryvIQ’s Kubernetes-based distributed applications. Build API, integration, system, UI, regression, and end-to-end coverage; improve frameworks, reusable utilities, diagnostics, test data, and CI/CD integration. Validate microservices, asynchronous workflows, deployments, upgrades, recovery, and enterprise integrations. Diagnose complex failures using logs and system evidence, collaborate with engineering and QA teams, contribute to Python/PyTest tooling, and provide technical guidance.

Design, develop, test, deploy, and operate scalable production software for content intelligence, metadata, classification, and data governance. Own backend services and significant features from design through production using C#/.NET, Linux, Kubernetes, databases, and web technologies. Diagnose performance and reliability issues, contribute to React-based experiences, optimize high-volume data systems, and support strong engineering practices within a growing Hyderabad team.

Lead and develop a 4–7 person software engineering team building C#/.NET backend microservices and distributed systems. Own architecture, delivery, production reliability, security, technical quality, hiring, coaching, and engineering practices. Partner with Product, QA, Security, Operations, and global teams while supporting DryvIQ and Nasuni integration. Remain technically hands-on through design reviews, code reviews, debugging, incident analysis, and selective development.

Provide hands-on technical leadership for scalable distributed services that discover, classify, govern, and activate enterprise unstructured data. Design and implement C#/.NET systems across Linux, Kubernetes, PostgreSQL, and ClickHouse; lead architecture, integration, performance, reliability, observability, and production troubleshooting. Guide engineers without formal management authority while contributing directly to code, reviews, prototypes, and technical decisions.

Build, deploy, and operate production backend and cloud services using Go, Python, AWS, and Terraform. Design event-driven and serverless systems, telemetry and analytics pipelines, and secure infrastructure. Own features through release, monitoring, incident response, and root-cause prevention. Improve CI/CD, observability, runbooks, and on-call practices while collaborating across global teams. Provide code reviews, technical guidance, and cross-functional support for enterprise data and cloud platforms.

Lead system and functional testing for distributed cloud and hybrid file-data services. Architect Python and PyTest automation infrastructure, validate performance, scalability, and reliability, analyze complex system issues, and champion testability and quality practices. Serve as a testing subject matter expert, mentor engineers, collaborate across product and engineering teams, and lead complex test initiatives with minimal supervision.

Designs and owns scalable CI/CD pipelines, distributed build and test infrastructure, release automation, and engineering workflows. The role improves pipeline reliability, performance, observability, test parallelization, and release quality across multiple teams. Responsibilities include troubleshooting complex infrastructure failures, evolving branching and versioning strategies, integrating quality gates, leading technical initiatives, mentoring engineers, and applying validated AI-assisted engineering workflows.