Top Artificial Intelligence Jobs in Hyderabad

Define and evolve scalable application architectures across backend, frontend, data, integrations, security, and cloud deployment. Establish engineering quality standards, testing practices, observability, and technical governance. Develop responsible AI-assisted software engineering guidelines, workflows, and quality controls. Provide hands-on technical leadership through architecture reviews, prototypes, reference implementations, critical code reviews, mentoring, and cross-team alignment.

Develop scalable Python and Flask applications, APIs, Azure cloud solutions, data pipelines, PostgreSQL databases, Redis integrations, and front-end components. Build agentic AI solutions, automated Playwright tests, and CI/CD processes while supporting secure coding, performance optimization, code reviews, troubleshooting, and production operations. Collaborate with product, architecture, DevOps, and security teams in an Agile environment.

Research Intern will investigate next-generation storage and memory architectures for AI/ML workloads. Responsibilities include working with NVMe and SPDK storage stacks, exploring memory tiering and disaggregation, evaluating near-storage computing techniques, and prototyping high-performance storage architectures. The role involves performance, scalability, and efficiency analysis, collaboration with senior researchers, and potentially publishing findings.

Design and maintain high-throughput backend services and concurrent asynchronous workflows using Python and Go. Build control-plane integrations with secure execution environments, scalable gRPC and REST APIs, and systems that process evaluation and event data. Collaborate across teams, document technical designs, review code, test systems, monitor performance, investigate bottlenecks, and improve reliability for distributed AI-agent orchestration platforms.

Designs, builds, and owns scalable SaaS features using .NET/C#, APIs, databases, cloud services, and modern UI frameworks. Leads technical design, testing, compliance, security, production health, incident response, and cross-functional delivery. Uses AI-assisted development tools while validating generated code for security, reliability, scalability, and data integrity. Requires strong system design, communication, and engineering judgment, with opportunities to develop AI-enabled engineering automation.

The role involves developing full-stack web apps, creating APIs, improving lead capture models, and collaborating across teams to enhance the Social Planner product.

Owns end-to-end development of significant SaaS product features using .NET/C#, cloud services, APIs, databases, and modern UI frameworks. Responsibilities include architecture, technical design, testing, compliance, threat modeling, production monitoring, incident response, and collaboration with product and design teams. The role also uses and evaluates AI-assisted development tools while ensuring security, reliability, scalability, and data integrity.

Own the end-to-end design, development, testing, deployment, and production health of scalable SaaS features using .NET/C#, cloud services, APIs, databases, and modern UI frameworks. Lead technical design, architecture, compliance, security, monitoring, incident response, and cross-functional delivery. Apply AI-assisted development tools responsibly while reviewing generated code for security, reliability, scalability, and data integrity.

Owns end-to-end development of significant SaaS product features using .NET, cloud services, APIs, databases, and modern UI frameworks. Responsibilities include system design, architecture, testing, compliance, security, production health, incident response, and collaboration with product and design teams. The engineer also uses and evaluates AI-assisted development tools while communicating technical decisions and driving reliable, scalable solutions.

Build and maintain AI-assisted quality infrastructure, including API and UI automation frameworks, CI/CD pipelines, test reporting, dashboards, alerting, and failure triage systems. Troubleshoot flaky tests and environment issues, support product scrum teams, review code, and promote effective AI-assisted engineering practices. The role emphasizes software engineering and internal platform development rather than direct product testing, machine learning, or data science.

Lead DevOps engineering for AI-enabled software solutions using C#, .NET, and Azure. Responsibilities include designing and maintaining cloud infrastructure, CI/CD pipelines, monitoring, security controls, and production-ready AI platforms. The role provides technical leadership and mentorship, resolves complex engineering issues, drives feature delivery, improves processes, and ensures scalable, reliable, and compliant solutions. Key focus areas include Azure OpenAI, RAG pipelines, agentic frameworks, observability, infrastructure as code, data governance, and secure Azure architecture.

Manage and optimize multi-cloud infrastructure (Azure, AWS, GCP), support AI/ML workloads, implement IaC and CI/CD, automate operations, ensure cloud security and compliance, and collaborate across teams while providing on-call and documentation support.

Develop and implement numerical and computational models (structure, materials, process) to support DRAM and NAND node development. Collaborate with process and product teams, create modeling tools and algorithms, analyze results, and present insights to engineering teams and leaders for silicon implementation.

Manage backend software development teams building reliable, scalable applications with Node.js and TypeScript. Lead system integrations across cloud and on-premises environments, oversee APIs, databases, transaction handling, failure recovery, validation, retries, and cloud services. Support AI and machine learning capabilities, distributed system architecture, security, troubleshooting, and performance optimization. The role is primarily based in Hyderabad with remote flexibility and requires collaboration across departments.

Designs and develops scalable cloud-based and serverless software across the company’s platform. Builds prototypes and production services, applies AI throughout the SDLC, promotes modern Agile and Well-Architected practices, troubleshoots customer and internal issues, develops comprehensive test suites, and coaches software engineers. The role requires extensive distributed application experience and backend expertise across multiple programming languages, databases, cloud technologies, integrations, and workflow orchestration.

Participate in full-stack development and maintenance of Binance’s KYC system, including backend services, frontend features, documentation, testing, regression, troubleshooting, and customer issue resolution. The role is a 3–6 month accelerator internship for current university students and recent graduates, with an emphasis on Java, Spring Boot, databases, middleware, and frontend technologies.

Develop and maintain a production AI SaaS platform across frontend, backend, databases, AI workflows, automation, and infrastructure. Responsibilities include resolving production issues, enhancing content-generation and chatbot features, managing AI memory and personalization, building n8n workflows and API integrations, supporting deployments, monitoring services, and maintaining technical documentation. The role requires independent debugging, AI-assisted development, and close collaboration with founders to ship product improvements.

Develop and maintain Python applications, APIs, workers, integrations, and AWS Lambda functions. Manage AWS and Linux environments, infrastructure automation, deployments, CI/CD pipelines, and production support. Improve reliability through monitoring, canary releases, rollback, and recovery practices. Maintain databases, messaging, authentication, security, dependencies, and external integrations. Apply AI-assisted development tools with human review and security validation. The role requires ownership of software delivery from application code through production.

The ServiceNow Solution Architect - AI role involves leading and mentoring a team, designing and deploying AI-driven applications, managing application development, and integrating solutions into ServiceNow modules. Responsibilities include coordinating with stakeholders, troubleshooting, and ensuring adherence to technical standards.

Own the CRM Opportunities backend end to end, designing scalable data models, APIs, distributed workflows, event-driven services, and background jobs. Improve performance and reliability across large multi-tenant pipelines while handling consistency, caching, sharding, observability, and incident response. Build AI-assisted CRM features using existing LLM APIs, including context assembly, response handling, cost and latency controls, and graceful degradation. Occasionally ship Vue.js UI changes and operate services through deployment and on-call.

Design, develop, and maintain scalable automation frameworks for web applications, APIs, and end-to-end workflows. Build API automation, integrate testing with CI/CD pipelines, and apply Generative AI, AI Agents, prompt engineering, and intelligent analysis to improve test coverage and quality. Collaborate across the SDLC, evaluate emerging automation technologies, and lead automation initiatives from design through implementation.

Design, develop, test, troubleshoot, and maintain scalable .NET applications using C# within an established codebase. Own features through the full software development lifecycle, translate requirements into implementations, resolve issues across applications, databases, and integrations, and participate in Agile planning, estimation, code reviews, and delivery. Maintain unit tests and technical documentation while collaborating with QA and stakeholders and proactively managing technical risks.

Designs, develops, tests, troubleshoots, and maintains scalable .NET applications using C# and SQL Server. Owns features through the full software development lifecycle, works within established codebases, resolves complex application and integration issues, participates in Agile ceremonies and code reviews, and collaborates with QA and stakeholders to deliver reliable software.

Analyze and reverse-engineer PowerBuilder applications, then support their migration to .NET and C#. Develop, test, troubleshoot, and document replacement functionality while analyzing SQL Server dependencies, integrations, and migration risks. Collaborate with QA and cross-functional Agile teams on functional equivalence, code reviews, estimation, sprint planning, and technical documentation.

Develop scalable enterprise applications and REST APIs using Python or .NET/C#, integrate Azure and Microsoft Fabric services, build SQL-based data and ETL/ELT solutions, and support Lakehouse, OneLake, and Data Warehouse architectures. Integrate LLMs and RAG capabilities into enterprise applications, troubleshoot application and data-pipeline issues, and collaborate with product, data, AI, and business teams. Backend and integration development are the primary focus, with working knowledge of modern front-end frameworks expected.