Top Engineering Jobs in Hyderabad

Lead full-chip or large-block physical implementation from netlist to GDSII. Drive floorplanning, placement, CTS, routing, STA timing closure, DRC/LVS/EM/IR signoff, ECOs, hard-macro integration, PPA optimization, and automation scripting while collaborating with RTL, architecture, verification, and foundry teams.

Design and implement RTL and microarchitectural components for SoC/IP using SystemVerilog/Verilog. Optimize PPA, collaborate with verification and physical design teams, support integration, timing closure, simulation, GLS, and silicon bring-up, and contribute to design documentation and reviews.

The role involves leading a team of Physical Design engineers in delivering high-performance silicon products while ensuring adherence to timing, power, and area requirements. Responsibilities include technical leadership, hands-on ownership of critical blocks, automation development, and stakeholder management to meet project milestones.

Design, develop, test and document PeopleSoft HCM (and FSCM) solutions to support legislative, tax and regulatory changes. Translate requirements into scalable solutions, collaborate within Agile Scrum teams, analyze complex issues, ensure compliance and quality, and support clients with clear documentation.

The DevOps Engineer will enhance software development processes, automate deployments, manage AWS infrastructure, and ensure system reliability.

As a Frontend Developer, you will develop and maintain web applications, design user-friendly interfaces, collaborate on requirements, and participate in Agile processes while ensuring code quality and performance.

As a Data Engineer, you will build scalable ETL/ELT pipelines, optimize data structures, and develop impactful Power BI solutions for stakeholders.

The AI Engineer will develop and deploy AI/ML models and solutions, collaborate with teams, and ensure production readiness while addressing complex business problems.

Design, develop, and maintain software applications using Netsuite and SuiteCommerce. Collaborate with teams, ensure quality through testing, and optimize performance.

As a Full Stack Developer, you will design and develop web applications using both front and back-end technologies, collaborating with teams to deliver high-quality solutions.

As a DevOps Engineer (GCP), you will automate and streamline software delivery processes while managing GCP infrastructure to ensure reliability and scalability.

Lead development and implementation of preventive and predictive maintenance for onshore mechanical equipment, use CMMS to plan and monitor maintenance, analyze reliability data, perform RCA, support operations and maintenance teams, ensure safety and compliance, and recommend improvements to reduce downtime and costs.

Build and maintain LLM-powered applications and MCP servers, implement tool/function calling and prompt pipelines, rapidly prototype new AI tools, track AI tool releases, and deliver weekly intelligence reports with demos and recommended integrations.

Lead development and implementation of preventive and predictive maintenance programs for offshore mechanical equipment, use CMMS to plan and track work, perform RCA for failures, support offshore teams in troubleshooting, monitor equipment reliability, and ensure compliance with safety and maintenance standards.

Build and maintain an AI-native EHR: own features end-to-end, ship continuously, use AI/LLMs to increase productivity, ensure reliability, and work across frontend, backend, data, jobs, and infra.

Design, develop, and maintain scalable Playwright/Cypress automated test frameworks and suites for web applications. Create and run functional, regression, integration, smoke, and end-to-end tests; integrate tests into CI/CD; debug failures; document defects and quality risks; mentor junior QA engineers; and improve automation coverage, reliability, and test speed.

Build and optimize core backend systems enabling user features, real-time data synchronization (event-driven/CDC), advanced caching and connection pooling, and improved observability. Drive architectural and infrastructure upgrades, own deployment and scaling strategies, contribute to open-source, and raise backend engineering standards across the platform.

Customer-facing technical role deploying AI-enabled solutions into enterprise environments: prototype, integrate, configure, and deliver AI-native workflows, ETL pipelines, dashboards, and tooling to improve ESG reporting, automation, and operational efficiency.

Design and build a greenfield, multi-layer data warehouse and semantic metrics layer; separate analytics from OLTP; ensure data quality, traceability, tenant isolation, and high SLAs; enable linking of structured records to drone imagery/video; deliver self-service data access, observability, and infrastructure automation to scale across products and tenants.

Develop low-level systems for a layer-1 blockchain focusing on performance and collaboration in design and iteration processes.

Design and build production LLM-based agent systems, governance knowledge pipelines, hybrid retrieval and evaluation frameworks, and platform infrastructure. Implement behavioral shaping, observability, and constraints to ensure agents align with governance and compliance requirements, collaborating with product and data teams.

As a Full Stack Engineer, you'll build user-friendly features and robust systems, collaborate with teams, maintain APIs, and ensure platform security and scalability.

Design, develop, and maintain scalable backend systems, ensuring performance, security, and scalability while collaborating with team members and optimizing code quality.

Work with engineering and product teams to embed quality from design through production: define test strategy, write and maintain automated UI/API/contract/integration tests (TypeScript/Puppeteer), use AI-assisted testing, run security and accessibility checks, maintain CI/CD quality gates, monitor post-deploy health, report defects and quality metrics, and mentor junior QAs.

Provide hands-on technical support to customers deploying, operating, and scaling ArangoDB-based AI systems. Diagnose issues, optimize queries and performance, configure deployments across Kubernetes and cloud/on-prem, debug networking/storage, script automations, and document solutions while collaborating with Product and Engineering.