Money Forward, Inc.
Senior Golang Engineer — AI-Era Software Development (Chennai / Pune)
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Design, develop, and operate scalable cloud-native systems using Go, concurrency, distributed systems, REST APIs, microservices, SQL, AWS, Docker, and Kubernetes. Lead releases, CI/CD, testing, troubleshooting, observability, and production improvements. Use and govern AI-assisted development tools, review AI-generated outputs, mentor engineers, improve team workflows, and collaborate with Product, QA, DevOps, and operational stakeholders.
Position overview
We are seeking a Senior Golang Engineer to design, develop and operate scalable cloud-native systems while leveraging AI to improve delivery speed, quality and team productivity.
You will bring strong expertise in Go, concurrent programming and distributed systems. You will work with Product, QA and DevOps stakeholders to translate business needs into reliable solutions, use AI to accelerate appropriate development activities, and take responsibility for verifying the quality and safety of the results.
You will also help the team adopt effective AI-assisted workflows, maintain clear technical context and continuously improve how we deliver customer value.
Key responsibilities
Software design and development
- 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.
AI-assisted delivery
- 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.
Quality, operations and delivery
- 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.
Leadership and collaboration
- 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
Required qualifications
- 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.
Preferred qualifications
- 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.
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