Top Software Engineer Jobs in India

Build and ship production-ready agentic AI applications using LLM tooling, RAG pipelines, vector search, enterprise API integrations, and evaluation frameworks. Develop clean, testable software, CI/CD pipelines, observability, guardrails, safety controls, and robust integrations. Rapidly prototype, demonstrate, iterate, and communicate technical tradeoffs while evolving solutions into scalable production systems.

Leads software architecture and engineering teams in building AI-enabled, production-ready systems. Provides architectural direction, technical governance, design specifications, code reviews, mentoring, and recommendations for reliability, scalability, platform convergence, and application improvement. Collaborates with product managers, stakeholders, executives, and development teams while driving cloud, DevOps, AI modernization, microservices, REST API, and multi-cloud initiatives.

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 engineering best practices for quality, scalability, compliance, testing, and documentation. Collaborate with architects and AI specialists while using Java full-stack development, cloud-native technologies, APIs, databases, and CI/CD pipelines to accelerate software delivery.

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 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, debugging, testing, documentation, and integration.

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, testing, and continuous improvement. Collaborate with architects and AI specialists while using copilots and LLM coding assistants to accelerate delivery.

Design and lead software architecture across engineering teams, including technical specifications, architectural governance, platform convergence, reliability, scalability, and system enhancements. Mentor developers, lead design sessions, conduct code reviews, and guide delivery of product features. Apply modern languages, microservices, REST APIs, cloud, DevOps, infrastructure as code, AI modernization, and security architecture to improve software quality and business outcomes.

Build and ship production-ready full-stack enterprise applications using AI-assisted development tools. Develop Java backend and modern frontend components, integrate AI services and APIs, implement RAG features, and apply software engineering best practices across coding, testing, documentation, integration, quality, and compliance. Collaborate with architects and AI specialists to accelerate delivery while maintaining scalable, reliable solutions.

Leads architectural direction for engineering teams while designing and delivering scalable, reliable software. The role includes technical governance, design specifications, platform convergence, code reviews, mentoring, cloud and AI modernization, microservices and REST API development, DevOps, infrastructure as code, and translating LLM innovation into business impact.

Leads the design, development, and delivery of production-ready SaaS software using AI-native engineering practices. Provides technical direction, oversees complex projects, mentors engineers, establishes architecture and technology choices, and collaborates with product and business stakeholders. Requires expertise in .NET full-stack development, cloud platforms, DevOps, CI/CD, containers, infrastructure as code, databases, security, AI modernization, and LLM-enabled engineering workflows.

Build and ship production-ready software using AI-native engineering practices. Provide architectural direction, lead design sessions, conduct code reviews, drive architectural governance, and mentor development teams. Design scalable systems and microservices, develop REST APIs, support cloud and DevOps modernization, and improve reliability, security, and engineering processes. Collaborate with product managers, stakeholders, and executive leadership to translate technical and AI innovation into business impact.

Design and deliver enterprise-grade full-stack applications using Java and AI-assisted development tools. Architect front-end and back-end solutions, integrate LLM services, RAG, conversational APIs, and copilots, and ensure security, compliance, scalability, and reliability. Collaborate with traditional engineering and AI-native teams to improve software delivery. The role focuses on AI integration and engineering productivity rather than model training or MLOps.

Build and ship production-ready software using AI-native engineering practices. Provide architectural direction, design scalable and reliable systems, lead technical design sessions, conduct code reviews, mentor engineers, and drive architectural governance. Develop .NET full-stack solutions using microservices, REST APIs, cloud, DevOps, infrastructure as code, and AI modernization approaches. Collaborate with product, engineering, and executive stakeholders to improve delivery, platform convergence, quality, security, and business impact.

Build and ship production-ready software using AI-native engineering practices. Lead architecture and technical direction for SaaS products, oversee delivery, mentor engineers, collaborate with stakeholders, and drive cloud, DevOps, automation, and AI modernization initiatives. The role requires .NET full-stack development, cloud platforms, CI/CD, containerization, infrastructure as code, database expertise, security practices, and strong technical leadership.

Leads the design, development, and delivery of production-ready SaaS software using .NET and AI-native engineering practices. Provides technical direction, architecture guidance, project oversight, mentorship, and stakeholder collaboration. Requires expertise in cloud platforms, DevOps, CI/CD, containers, infrastructure as code, databases, security, and software design. The role also drives AI modernization, automation, LLM adoption, product ownership, and innovation across engineering teams.

Lead and contribute to the design, development, and delivery of production-ready SaaS software using AI-native engineering practices. Provide technical direction, architecture guidance, project oversight, and mentorship while collaborating with product and business stakeholders. Build .NET full-stack solutions, cloud platforms, CI/CD pipelines, containerized services, and infrastructure as code. Drive AI modernization, automation, quality, security, and compliance initiatives while translating AI capabilities into measurable business and productivity outcomes.

Build and ship production-ready AI-enabled software using .NET full-stack development. Provide architectural direction, lead technical design and governance, mentor engineers, conduct code reviews, and improve system reliability, scalability, and quality. Collaborate with product and engineering stakeholders on modernization, microservices, REST APIs, cloud, DevOps, and AI initiatives. Translate AI innovation into business impact while supporting continuous delivery and platform convergence.

Build and ship production-ready software using AI throughout the engineering lifecycle. Lead architecture and technical direction for SaaS products, oversee delivery, mentor engineers, collaborate with stakeholders, and drive innovation. The role requires .NET full-stack development, cloud platforms, DevOps, CI/CD, containerization, infrastructure as code, database architecture, security practices, and understanding of LLMs and automation.

Leads architecture and software engineering initiatives while building production-ready AI-enabled applications. Provides technical direction, conducts design reviews and code reviews, drives architectural governance, improves system reliability and scalability, mentors developers, and collaborates with product and engineering stakeholders. The role requires extensive .NET full-stack development, cloud and DevOps modernization, microservices, REST APIs, infrastructure as code, and applying LLMs and automation to improve software delivery.

Build and ship production-ready software using AI-native engineering practices. Provide architectural direction, lead design sessions, conduct code reviews, mentor developers, and drive architectural governance. Design scalable systems, microservices, REST APIs, cloud and DevOps solutions, and AI modernization initiatives. Collaborate with product managers and engineering teams, improve application quality and reliability, and translate LLM and automation innovations into business impact.

Build and ship production-ready software using AI-native engineering practices. Provide architectural direction, design scalable and reliable systems, lead technical design sessions, conduct code reviews, mentor developers, and drive architectural governance. Develop microservices and REST APIs while supporting cloud, DevOps, AI modernization, continuous delivery, infrastructure as code, and multi-cloud initiatives. Collaborate with product managers, engineering teams, stakeholders, and executives to improve software quality, delivery, and business impact.

Build and ship production-ready software using AI-native engineering practices. Provide architectural direction, lead design and governance, guide microservices and API development, improve reliability and scalability, and mentor engineering teams. Collaborate with product managers and stakeholders on technical strategy, platform convergence, cloud and DevOps modernization, continuous delivery, infrastructure as code, and translating AI and LLM capabilities into business and productivity improvements.

Build and ship production-ready software using AI throughout the engineering lifecycle. Lead technical architecture and delivery of SaaS applications, mentor engineers, establish engineering standards, and collaborate with product and business stakeholders. The role requires .NET full-stack development, cloud platforms, CI/CD, containerization, infrastructure as code, databases, security practices, and AI modernization experience, including LLMs and automation.

Lead and mentor engineering teams while designing, developing, and delivering production-ready SaaS software using .NET, cloud platforms, DevOps, and AI-native practices. Set technical direction, oversee complex projects, guide architecture and technology choices, collaborate with stakeholders, and drive innovation. The role requires hands-on software engineering, cloud modernization, CI/CD, containerization, infrastructure as code, database expertise, security awareness, and the ability to translate AI and LLM innovations into business impact.

Lead the architecture, development, and delivery of production-ready SaaS software using AI-native engineering practices. Guide technical direction, oversee complex projects, mentor engineers, collaborate with stakeholders, and drive innovation. Develop .NET full-stack solutions using cloud platforms, CI/CD, containers, infrastructure as code, databases, and security best practices. Translate AI, LLM, automation, and modernization initiatives into business and productivity improvements while balancing product goals and delivery outcomes.

Architect and lead the development of production-ready, AI-enabled software using .NET full-stack technologies. Provide architectural direction, design scalable systems and microservices, drive governance and platform convergence, conduct code reviews, mentor engineers, and collaborate with product and executive stakeholders. Apply cloud, DevOps, infrastructure-as-code, LLM, automation, security, monitoring, and continuous delivery practices to improve software quality, reliability, compliance, and business impact.