Top Software Engineer Jobs in India

Build production-ready agentic AI applications using LLM tooling, RAG pipelines, vector search, AI APIs, and enterprise integrations. Develop agents, prompts, memory, evaluation loops, testing, CI/CD, observability, guardrails, and safety controls. Rapidly prototype and evolve solutions into reliable production systems while communicating tradeoffs with stakeholders. The role requires Java full-stack experience, strong software engineering fundamentals, hands-on AI development, and a demonstrable portfolio of AI projects.

Build production-ready full-stack enterprise applications using AI-assisted development tools, LLMs, and prebuilt AI services. Develop frontend and backend components, integrate APIs, implement RAG features, and apply software engineering best practices for quality, scalability, compliance, and rapid delivery. Collaborate with architects and AI specialists while continuously improving AI-native development workflows.

Leads the design, development, testing, and support of production-ready AI-native software and scalable web services. Provides technical direction, architecture and code reviews, mentoring, knowledge transfer, and continuous improvement of codebases and engineering practices. Builds Java full-stack solutions using cloud infrastructure, DevOps, distributed systems, big data, automation, and LLM technologies. Collaborates across product, engineering, and customer support teams while driving technical decisions, quality, security, compliance, and business impact.

Build and maintain production-ready Java full-stack software and scalable web services using AI-native engineering practices. Lead technical design, architecture, implementation, testing, debugging, code reviews, and cloud DevOps initiatives. Improve existing systems, ensure quality and compliance, mentor developers, support customers, and collaborate across teams. The role requires experience with distributed systems, cloud infrastructure, databases, CI/CD, security, testing, AI modernization, and translating AI capabilities into business impact.

Build and ship production-ready software using AI-native engineering practices. Design, implement, test, maintain, and improve scalable Java full-stack applications and distributed systems. Lead architecture and code reviews, develop cloud-based SaaS solutions, improve quality and compliance, troubleshoot technical issues, mentor engineers, and collaborate with cross-functional teams. The role requires strong Java, cloud infrastructure, DevOps, testing, web services, database, and AI modernization experience.

Build and ship production-ready full-stack enterprise applications using AI-assisted development tools. Develop frontend and backend components, integrate AI services and APIs, implement RAG features, and apply software engineering best practices for quality, scalability, compliance, and delivery speed. Collaborate with architects and AI specialists while using copilots and LLM-based tools for coding, testing, debugging, documentation, and integration.

Build and ship production-ready software using AI throughout the engineering lifecycle. Lead architecture, design, implementation, testing, maintenance, and support of scalable Java-based web services and distributed systems. Drive cloud, DevOps, and AI modernization initiatives; improve code quality, security, performance, and operational practices. Collaborate across functions, conduct design and code reviews, mentor engineers, investigate emerging technologies, and translate AI innovations into business and productivity outcomes.

Build and ship production-ready full-stack enterprise applications using AI-native development practices. Develop front-end and back-end components, integrate AI services and APIs, implement RAG features, and use copilots and LLM tools for coding, testing, debugging, and documentation. Collaborate with architects and AI specialists while maintaining scalability, quality, compliance, and delivery speed.

Build and ship production-ready AI-native applications using LLMs, agents, RAG pipelines, vector databases, enterprise APIs, and evaluation frameworks. Develop clean, testable software, CI/CD pipelines, observability, guardrails, and safety controls. Prototype rapidly, integrate AI into enterprise systems, conduct testing and red-team evaluations, and communicate technical tradeoffs to stakeholders. Requires at least 7.5 years of Java full-stack development experience and strong hands-on AI engineering skills.

Build and maintain production-ready Java full-stack software using AI-native engineering practices. Responsibilities include technical design, scalable web-service architecture, implementation, testing, debugging, code reviews, system improvements, cloud and DevOps work, documentation, customer support, and mentoring. The role requires leading complex technical initiatives, guiding architecture and design decisions, integrating cloud and data technologies, and translating AI innovation into business and productivity improvements.

Build and ship production-ready AI-native software, primarily using Java full-stack development. Responsibilities include designing, implementing, testing, maintaining, and supporting scalable web services; leading architecture and code reviews; improving system quality; mentoring developers; and driving cloud, DevOps, AI modernization, and distributed-systems initiatives. The role requires collaboration across technical and business teams, independent decision-making, and translating AI innovation into measurable business and productivity impact.

Build and maintain production-ready Java full-stack software using AI-native engineering practices. Lead architecture, design, implementation, testing, debugging, and code reviews for scalable distributed systems and cloud-based SaaS products. Develop technical specifications, improve existing codebases, support customers, investigate technologies, and drive quality and compliance. Mentor developers and collaborate across product, engineering, and customer-facing teams while leading cloud, DevOps, AI modernization, and technical strategy initiatives.

Build and ship production-ready software using AI-native engineering practices. Design, implement, test, maintain, and improve scalable Java full-stack applications and web services. Lead architecture and code reviews, troubleshoot distributed systems, support CI/CD and cloud infrastructure, and ensure quality, security, and compliance. The role includes technical design, cross-functional collaboration, mentoring developers, evaluating new technologies, and translating AI, LLM, automation, and modernization initiatives into business impact.

Build and ship production-ready agentic AI applications using LLM tooling, RAG pipelines, vector search, enterprise APIs, and AI integrations. Develop agents, prompts, memory, evaluation loops, testing, CI/CD, observability, guardrails, and safety controls. Rapidly prototype and evolve solutions into scalable production systems while communicating trade-offs with stakeholders. Requires strong software engineering fundamentals, Java full-stack experience, hands-on AI development, and a portfolio demonstrating experimentation and end-to-end delivery.

Leads the design, development, testing, deployment, and support of scalable Java full-stack software and distributed systems. Defines technical architecture, reviews requirements and code, improves system quality, mentors engineers, and guides cross-functional delivery. The role applies AI-native engineering practices, cloud infrastructure, DevOps, automation, LLMs, and modern software toolchains to build production-ready solutions and improve engineering productivity.

Build and ship production-ready software using AI-native engineering practices. Design, implement, test, maintain, and improve scalable web services and distributed systems using Java full-stack development. Lead architecture and code reviews, support cloud infrastructure and CI/CD, debug complex systems, improve quality and security, and collaborate with cross-functional teams. The role also involves mentoring developers, evaluating emerging technologies, and translating AI, automation, and LLM capabilities into business and productivity impact.

Build and ship production-ready full-stack enterprise applications using AI-assisted development tools. Develop front-end and back-end components, integrate AI services and APIs, implement RAG features, and apply software engineering, quality, compliance, and SDLC best practices. Collaborate with architects and AI specialists to accelerate delivery while maintaining scalable, reliable solutions.

Lead the design and implementation of production AI and deep learning systems using LLMs, Python, .NET, and Azure. Drive technical strategy, architecture decisions, team mentorship, cloud-native development, MLOps, CI/CD, and scalable microservices deployment. Collaborate with product and data science teams to deliver business-focused AI solutions and continuously improve engineering practices.

Build and ship production-ready full-stack enterprise software using AI-assisted development tools. Develop frontend and backend components, integrate AI services and APIs, implement RAG features, and use copilots and LLM tools for coding, testing, debugging, and documentation. Collaborate with architects and AI specialists while maintaining scalability, quality, compliance, and engineering best practices.

Build and ship production-ready agentic AI applications using LLMs, RAG pipelines, vector databases, AI APIs, and enterprise integrations. Develop agents, prompts, memory, evaluation loops, testing, CI/CD pipelines, observability, guardrails, and safety controls. Rapidly prototype and evolve solutions into reliable production systems while communicating tradeoffs and results to stakeholders. The role requires strong software engineering fundamentals, Java full-stack experience, hands-on AI development, and a portfolio demonstrating experimentation and end-to-end delivery.

Build and ship production-ready full-stack enterprise applications using AI-assisted development tools, LLMs, pre-built AI services, and RAG features. Develop Java-based backend and modern frontend components, integrate APIs, apply software engineering and SDLC best practices, maintain quality and compliance, and collaborate with architects and AI specialists to accelerate delivery.

Build and ship production-ready enterprise software using AI-assisted development tools. Develop integrated front-end and back-end components, incorporate AI services and APIs, implement RAG features, and deliver scalable applications through strong engineering and SDLC practices. Collaborate with architects and AI specialists while maintaining quality, compliance, testing, documentation, and delivery speed.

Build and maintain production-ready AI-native software using Java full-stack development. Lead technical design, architecture, implementation, testing, code reviews, debugging, and system improvements. Work with cloud infrastructure, CI/CD, scalable web services, databases, DevOps, LLMs, and AI modernization initiatives. Mentor developers, provide technical guidance, support customers, and collaborate across product and engineering teams.

Build and ship production-ready enterprise software using AI-assisted development practices. Develop full-stack frontend and backend applications, integrate AI services and APIs, implement RAG features, and use LLM copilots for coding, testing, debugging, and documentation. Collaborate with architects and AI specialists while maintaining scalability, quality, compliance, and SDLC best practices.

Build and ship production-ready full-stack enterprise applications using AI-assisted development tools. Develop frontend and backend components, integrate AI services and APIs, implement RAG features, and deliver scalable, compliant software using engineering best practices, cloud-native technologies, and CI/CD. Collaborate with architects and AI specialists to improve development speed and quality.