Role Description This role is for a Software Development Engineer (Tech Lead) within GoDaddy’s engineering organization, focused on building scalable, fault-tolerant systems that power critical customer and platform experiences at massive scale. - Work on highly impactful engineering initiatives, including greenfield projects and open-ended problem spaces. - Bring structure, technical leadership, and strong execution to the team. - Serve millions of users with high standards around reliability, scalability, and operational excellence. - Drive architectural decisions, mentor engineers, and shape engineering best practices across multiple applications and services. - Value innovation, continuous improvement, and practical adoption of emerging technologies. - Opportunity to work on complex distributed systems and influence engineering direction. Qualifications - 8+ years of professional software engineering experience building and operating production-grade systems. - Strong proficiency across modern backend technologies with expertise in GoLang, Python, or Node.js. - Hands-on AWS experience across services such as EKS, ECS, Fargate, Lambda, S3, SQS/SNS, RDS/Aurora, and IAM. - Strong experience designing and operating distributed, fault-tolerant, highly available systems. - Hands-on experience with PostgreSQL/Aurora and MongoDB including schema design, indexing, and query optimization. - Experience implementing observability and monitoring solutions using tools such as CloudWatch, Prometheus, Grafana, or Datadog. - Experience with Infrastructure-as-Code tools such as Terraform, CDK, or CloudFormation. - Hands-on experience integrating AI/ML tooling or LLM-powered capabilities into production systems or engineering workflows. - Deep understanding of Agile/Scrum principles and experience driving engineering process improvements. - Ability to operate effectively in ambiguous and evolving problem spaces. - Proven technical leadership experience driving projects end-to-end and mentoring engineers. Requirements - Lead technical design discussions for complex cross-service architectures and platform capabilities. - Drive architectural decisions balancing scalability, reliability, operational simplicity, and long-term maintainability. - Build systems with strong observability practices including monitoring, alerting, logging, and distributed tracing. - Identify and mitigate technical risks early in the development lifecycle. - Serve as a trusted technical leader and subject matter expert for complex engineering challenges. - Lead agile development practices including sprint planning, retrospectives, code reviews, and collaborative design sessions. - Mentor junior and mid-level engineers on system design, code quality, and engineering best practices. - Foster a culture of ownership, continuous learning, and engineering excellence across the team. - Drive adoption of AI-assisted engineering workflows across development, testing, and documentation processes. - Explore and implement AI/ML capabilities within engineering and product workflows. - Promote experimentation with modern technologies and emerging engineering practices. Benefits - Paid time off. - Retirement savings (e.g., 401k, pension schemes). - Bonus/incentive eligibility. - Equity grants. - Participation in employee stock purchase plan. - Competitive health benefits. - Family-friendly benefits including parental leave.

Role Description We are looking for experienced Senior Software Engineers (.NET Full Stack Developers) to design and build scalable, high-performance applications. You will play a critical role in developing modern backend systems, APIs, and front-end applications. Qualifications - 5 to 12 years of experience - Strong experience in .NET Core, C#, and ASP.NET - Frontend development using Angular, JavaScript, HTML, CSS, Bootstrap, jQuery - Database expertise with SQL Server (MS SQL) - Experience with Azure Cloud Services - Knowledge of Web APIs and Web Services - Hands-on experience with microservices and distributed systems - Understanding of event-driven architecture and system communication - Experience in system design and solution architecture - Proficiency using Visual Studio Requirements - Hands-on experience using AI-assisted development tools (e.g., GitHub Copilot or similar) - Understanding of LLMs (Large Language Models) and their practical limitations - Experience integrating AI into development workflows Key Responsibilities - Design and implement scalable backend systems, APIs, and microservices - Develop modern, responsive frontend applications - Act as a subject-matter expert in .NET, system performance, and scalability - Leverage AI tools in development workflows while ensuring code correctness and security - Follow secure-by-design principles and contribute to threat modeling practices - Build and maintain CI/CD pipelines with automated testing and quality checks - Collaborate with cross-functional teams (product managers, designers) to define technical roadmaps - Ensure system reliability through code reviews, monitoring, and optimization - Troubleshoot and resolve complex production issues - Drive cost optimization and cloud efficiency initiatives - Participate in Agile ceremonies including sprint planning and backlog refinement Benefits - 100% remote work environment - Flexible working culture (no strict time tracking) - Exposure to global clients and teams - Ownership-driven and performance-focused culture - Emphasis on work-life balance and collaboration - Group Mediclaim Insurance (up to INR 4,00,000 per annum for employee, spouse, and up to 2 children) - Group Personal Accident Insurance (INR 10,00,000 coverage) - Performance-based bonus (up to 10% on a pro-rata basis) Interview Process - Practical Assessment - Two Technical Rounds - Final Interview Work Timings 11:00 AM to 8:00 PM (IST)

Role Description We are seeking an experienced Semiconductor Software Engineer to design and build software tooling, firmware, and infrastructure that support semiconductor design, verification, manufacturing, and post-silicon validation. In this role you will partner with hardware engineers and EDA teams to build software that accelerates silicon development cycles and improves yield, performance, and quality. The ideal candidate will combine strong software engineering fundamentals with practical experience working alongside hardware teams in EDA, verification, or post-silicon environments. In this role you will work closely with cross-functional partners — product, design, engineering, operations, and business stakeholders — to translate ambiguous requirements into well-engineered solutions, and will be expected to raise the bar through code review, design review, and mentorship of more junior engineers. The successful candidate brings strong engineering discipline, a clear communication style, and a track record of shipping meaningful work that holds up well in production. Qualifications - Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related field. - Six or more years of software engineering experience, with significant time in semiconductor environments. - Strong programming skills in C, C++, and Python. - Hands-on experience with EDA, verification, or post-silicon validation workflows. - Solid understanding of hardware-software interaction at a low level. - Experience building large-scale compute infrastructure (grid, cloud, HPC). - Strong scripting and automation skills. - Experience with data pipelines for design or characterization data. - Excellent debugging and troubleshooting skills. - Strong communication and documentation skills. Requirements - Design and build software tooling that accelerates semiconductor design and verification workflows. - Develop firmware and low-level software interacting directly with silicon, including drivers and BSPs. - Build infrastructure to support large-scale EDA tool execution on compute farms and cloud platforms. - Develop post-silicon validation tooling, including high-throughput test orchestration, programmable stimulus generation, and result aggregation systems that scale across many parts and many test environments. - Build data pipelines for design, verification, and characterization data, supporting downstream analytics and ML. - Implement debug tooling and diagnostic infrastructure for hardware bring-up and silicon characterization, giving engineers fast feedback loops on the silicon-software interface during critical validation windows. - Partner with hardware engineers to translate hardware-specific requirements into clean software designs. - Optimize software for performance and scalability in compute-intensive semiconductor workflows. - Lead architecture and code reviews that span the software-hardware boundary, ensuring that abstractions, interfaces, and constraints between the two domains are well-understood and respected across the team. - Contribute to internal libraries and tooling shared across silicon design teams. - Maintain comprehensive, current technical documentation — including architecture diagrams, design decisions, configuration references, runbooks, and operational procedures — so that the system remains supportable, auditable, and easy to onboard new engineers onto over time. - Mentor and coach junior and mid-level engineers through code review, design review, pair programming, and structured knowledge sharing, helping the broader team grow in technical maturity and confidence over time. - Continuously evaluate emerging hardware platforms and toolchains, assessing maturity, fit for purpose, and total cost of ownership, and make grounded recommendations on which to adopt, pilot, or defer based on real engineering needs. Benefits - Competitive base salary commensurate with experience, plus benefits.

• Build production software – Design and implement scalable backend services, APIs, and data pipelines with a focus on reliability, performance, and maintainability • Develop agentic systems – Create autonomous agents that leverage LLMs to reason, use tools, and orchestrate complex multi-step workflows • Architect for scale – Design systems that handle real-time AI inference, conversation state, and tool execution with proper error handling and recovery • Design, develop, and deploy machine learning models that drive product features, improve user engagement, and enhance decision-making processes • Collaborate cross-functionally – Partner with Product, Design, and Engineering teams to define requirements and deliver AI-powered features. Maintain engineering excellence – Write clean, well-tested code; conduct thorough code reviews; champion best practices across the team • Stay current – Evaluate emerging agentic frameworks, patterns, and tools; prototype new approaches to solve real problems