Senior Golang Engineer — AI-Era Software Development (Chennai / Pune)

• Lead the design and development of scalable, performant and maintainable systems using Go, including concurrent and distributed applications.
  
• Design and manage RESTful APIs and microservices that integrate effectively with existing systems.
  
• Translate business and customer requirements into technical designs in collaboration with Product, QA, DevOps and other stakeholders.
  
• Define and address non-functional requirements, including security, scalability, performance, reliability and observability.
  
• Optimise SQL databases and queries for efficient data management and system performance.
  
• Identify technical risks early and develop practical mitigation plans.
  

• Use approved AI tools to support research, design, implementation, testing, documentation and troubleshooting throughout the development lifecycle.
  
• Apply sound judgment when deciding which tasks to delegate to AI and what level of human review and verification is required.
  
• Review, test and improve AI-generated code, tests and documentation. Remain accountable for the correctness, security and maintainability of delivered work.
  
• Use generative AI to create prototypes, clarify uncertain requirements and validate ideas quickly with stakeholders.
  
• Maintain clear specifications, architecture decisions and project documentation so that both engineers and AI tools can understand the relevant context.
  
• Follow company policies for AI usage, data protection, confidentiality and access permissions.
  

• Build and maintain cloud-native applications on AWS using appropriate container and infrastructure technologies.
  
• Develop and improve CI/CD pipelines using CircleCI or similar tools, and manage version control workflows through GitHub.
  
• Collaborate with QA to identify testing gaps and improve automated testing, including the appropriate use of AI-assisted test generation.
  
• Troubleshoot and resolve complex issues in development and production environments.
  
• Lead production releases, coordinating with relevant teams and improving future releases through feedback and lessons learned.
  
• Balance delivery speed, release quality and technical debt while considering impacts on existing systems and business workflows.
  
• Identify delivery bottlenecks and improve team workflows, using measures such as lead time, quality and throughput where appropriate.
  

• Mentor engineers through code reviews, design reviews, pair programming and knowledge sharing.
  
• Support team members in developing effective prompting, context-setting and AI-output review skills.
  
• Promote a culture of learning, experimentation, ownership and continuous improvement.
  
• Communicate technical decisions, risks and trade-offs clearly to technical and non-technical stakeholders.
  
• Contribute to technology and tool selection based on business value, team needs and long-term maintainability
  

Requirements

• 5+ years of software engineering experience, including 3+ years of Go development.
  
• Strong experience with Go concurrency, including goroutines, channels and concurrency control.
  
• Experience designing, troubleshooting and optimising scalable distributed systems.
  
• Experience with cloud-native technologies, particularly AWS, Docker and Kubernetes.
  
• Strong SQL skills, including database and query performance optimisation.
  
• Hands-on experience with CI/CD pipelines using CircleCI or similar tools and version control using GitHub.
  
• Experience designing and managing RESTful APIs or microservices.
  
• Experience leading production releases and collaborating across engineering, Product, QA and operational teams.
  
• Ability to use AI-assisted development tools effectively and critically evaluate their outputs.
  
• Strong understanding of software testing, code review and engineering practices needed to deliver reliable, maintainable software.
  
• Ability to work through ambiguity, learn new technologies and make sound technical decisions.
  
• Strong communication, mentoring and cross-functional collaboration skills.
  

• Experience using AI to support prototyping, test automation, documentation or development workflow improvements.
  
• Experience coaching others in AI-assisted development or introducing AI tools and practices to a team.
  
• Experience integrating LLM APIs into application workflows, including prompt design and handling asynchronous or non-deterministic responses.
  
• Experience building services that interact with AI agents or developing AI-enabled product features.
  
• Experience with monitoring and logging tools such as Prometheus, Grafana or the ELK Stack.
  
• Knowledge of security best practices for cloud-native environments.
  
• Familiarity with Kafka, RabbitMQ or other messaging technologies used in event-driven architectures.
  
• Experience with frontend development, such as React, or a willingness to work across relevant parts of the development lifecycle.