Top Engineering Jobs in Hyderabad

Build and maintain infrastructure and integrations that move CMS, SCADA, and other customer data into cloud platforms. Monitor and resolve connectivity issues, support AWS infrastructure, respond to data support tickets, collaborate with service delivery teams, and improve connectivity processes for scalability and reliability. The role requires Linux command-line expertise, knowledge of data protocols, networking, and IT security, plus flexibility to support global operations outside normal business hours.

Design, develop, and maintain scalable web applications using Node.js. Lead and mentor UI and backend engineers, collaborate with product and design teams, conduct code reviews, troubleshoot complex issues, and optimize application performance. The role also requires applying engineering best practices, working with RESTful APIs and cloud technologies, and staying current with industry trends. Preferred experience includes server-side rendering, Next.js, modern front-end build tools, performance optimization, and testing.

Build and own automated testing frameworks using Playwright and Selenium, automate API testing, and design load and performance tests. Develop maintainable BDD/Cucumber suites and use Claude to generate, debug, scale, and improve test automation. The role is hybrid in Hyderabad or Indore and supports products across fintech, healthcare, insurance, manufacturing, and other industries.

The Senior Platform Engineer will manage and build cloud-native infrastructures, develop backend features, ensure high availability, and interface with users while leveraging AI to enhance developer productivity.

Principal Data Engineer responsible for developing and supporting Databricks pipelines, integrating heterogeneous healthcare data sources, modeling unified data products, and ensuring data quality and availability. The role partners with business stakeholders, product teams, data engineers, and clinical leaders to gather requirements, create datasets, support ad hoc analytics, enable machine learning and AI use cases, and assist with acquisition integrations. Extensive healthcare data, cloud, SQL, PySpark, and Python experience is required.

Designs and maintains Playwright and JavaScript automation frameworks for UI, end-to-end, integration, functional, regression, and smoke testing. Validates REST APIs, troubleshoots defects, contributes QA input during Agile planning, and integrates automated suites into CI/CD pipelines. The role also maintains test documentation and collaborates with developers, business analysts, and product stakeholders to ensure quality across enterprise applications.

Design, build, and scale production AI agents across EveryWatch. Own the agent roadmap, architecture, shared tools, memory, state, observability, evaluation, and cost controls. Harden WatchChat, develop RAG and tool-calling systems, establish measurable quality standards, and ship solutions directly in Python. Collaborate with sales, product, data, and engineering teams to identify high-impact use cases and take agent concepts from discovery through production.

Design, build, and deploy AI/ML and Generative AI solutions for enterprise use cases. Build and maintain end-to-end ML pipelines, deploy models to production, and implement monitoring, observability, and model-drift detection. Work with APIs, vector databases, embeddings, and RAG-based applications, and collaborate with cross-functional teams to optimize scalable AI deployments.

Design, build, and optimize orchestrated data pipelines using dbt, Airflow, Azure Databricks, PySpark, SQL and Python. Implement CI/CD and automation, ensure data quality, perform ad-hoc analysis and reporting, collaborate with cross-functional teams, and troubleshoot DAG failures to support data-driven decision-making.

Validate AI voice bot functionality by creating/executing test cases from business documents, running functional/regression/integration/API tests, verifying conversational flows and intent recognition, supporting automation efforts, managing defects, and assisting production validation and release activities.

Lead design, build, deploy, and monitor enterprise-scale AI/ML and Generative AI systems. Own end-to-end ML pipelines, scalable inference, vector search and RAG applications, MLOps, observability, governance, CI/CD, model lifecycle management, and production support. Mentor teams, collaborate with stakeholders, and optimize AI systems for scalability, latency, reliability, and cost.

Design, build, and deploy production-grade AI applications integrated with LLMs to automate and optimize investment management workflows. Evaluate generative models, implement RAG and vector DB solutions, create automated workflows, collaborate with cross-functional teams, ensure security/compliance, and contribute to architecture, code reviews, and documentation.

Performs manual functional and regression testing, creates and executes test cases, reports and tracks defects, and conducts API testing using tools such as Postman or Swagger. Collaborates with development and product teams to support product quality. Requires practical API testing experience, knowledge of HTTP methods and status codes, familiarity with STLC and bug lifecycles, and understanding of Agile/Scrum practices.

Develop scalable full-stack web applications using modern frameworks, optimize performance, resolve bugs and vulnerabilities, maintain security documentation, implement automated testing, collaborate with product and engineering teams, and mentor junior developers and interns. The role also includes architecture, code reviews, cross-functional communication, and prioritizing development work aligned with business goals.

Own and scale AWS infrastructure, CI/CD, and cloud-native distributed systems supporting millions of users and real-time events. Responsibilities include Kubernetes and Docker environments, Terraform automation, GitHub Actions pipelines, observability, security, high availability, disaster recovery, and SaaS-to-on-prem deployments. The role also involves optimizing event ingestion, contributing to architecture decisions, collaborating across engineering teams, and leading DevOps initiatives.

Develop and deploy AI agents, integrations, automations, and workflow solutions for customers. Build knowledge graphs and connect SaaS and non-SaaS systems using APIs, webhooks, and real-time architectures. Optimize AI performance through prompt engineering and semantic search, analyze data with SQL, create dashboards, prototype solutions, conduct technical demonstrations, and collaborate across customer-facing and internal teams. The role involves approximately 30% customer engagement and up to 80% travel.

Supports the analysis, design, testing, troubleshooting, documentation, and lifecycle management of enterprise integration and automation solutions. Works with APIs, microservices, databases, B2B and supplier integrations, EDI, workflow automation, and data quality. Collaborates with stakeholders, architects, and developers to gather requirements, configure solutions, perform quality assurance, manage risks, resolve incidents, and maintain integration components and documentation.

Build and ship production-grade full-stack applications for agentic AI use cases. Own user experience, application architecture, enterprise security, permissions, agent safeguards, auditability, deployment, scalability, observability, and marketplace packaging. Translate complex AI and graph capabilities into intuitive investigation workflows, collaborate with customers and cross-functional teams, and create reusable, configurable products deployable across enterprise customers and cloud environments.

Design, implement, maintain, and operate highly available distributed systems for graph data and vector embedding infrastructure. Optimize ingestion, indexing, query, and nearest-neighbor search pipelines for low latency and high throughput. Diagnose production issues across the data stack, lead root-cause analyses, and implement preventive measures. Collaborate with teammates and adopt AI-assisted engineering practices.

Build and optimize backend systems for real-time and historical data querying. Responsibilities include developing query language runtimes, parsing, semantic analysis, query planning, execution, Kafka-native streaming pipelines, Spring Boot services, and high-performance Java and C++ components. Collaborate on database infrastructure, query optimization, language semantics, type systems, code reviews, and engineering standards.

Design, develop, test, and maintain Java/J2EE backend and frontend features. Build UI components with HTML, JavaScript, and CSS; optimize SQL and relational database interactions; participate in code reviews and unit testing; troubleshoot production issues; collaborate with QA, product, and engineering teams; and lead technical design discussions and documentation.

Develop and modernize ServiceNow applications, workflows, integrations, and user experiences. Responsibilities include custom application development, UI Builder and Workspace configuration, JavaScript and Glide API scripting, REST/SOAP integrations, Flow Designer automation, Service Catalog fulfillment, and maintaining ITSM and CMDB data integrity.

Deploys and engineers SIEM, EDR/XDR, SOAR, DLP, firewall, IAM, cloud, and zero-trust security platforms for MSSP/MXDR operations. Responsibilities include log onboarding, detection engineering, incident-response automation, endpoint and network hardening, cloud security, customer architecture workshops, technical presales support, platform monitoring, documentation, and Python-based automation. The role requires leading engineering initiatives and delivering production-grade security solutions across multi-tenant environments.

Build and deploy production-grade AI/ML systems spanning LLMs, RAG, agentic AI, computer vision, edge AI, and autonomous robotics. Responsibilities include model fine-tuning, distributed system architecture, GPU optimization, simulation-based robotics development using MuJoCo and Isaac, autonomous driving simulation, and end-to-end algorithm deployment. The role requires translating business problems into scalable AI products and contributing to commercialization and product-market fit.

Own end-to-end product features for a SaaS platform serving HR, therapists, and employees. Build, scale, and evolve frontend and backend components, lead architecture and standards, collaborate with design and product, and incorporate customer feedback and QA. Work in an early-stage startup environment with product-focused ownership.