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Diligent is seeking a Software Engineer II to build scalable backend services, APIs, integrations, and AI-enabled features that power their governance, risk, and compliance (GRC) SaaS platform. You will develop production software using Python and cloud technologies, contributing to solutions from design through deployment.
Key responsibilities include:
- Design and build scalable backend services, REST APIs, integrations, and reusable software components using Python and TypeScript
- Develop data ingestion, transformation, service-to-service communication, and automation capabilities
- Contribute to AI-enabled features and use AI development tools responsibly to improve coding, testing, research, documentation, and delivery
- Apply sound engineering practices across architecture, performance, security, testing, debugging, and maintainability
- Deploy and operate services using AWS and CI/CD workflows, contributing to monitoring, troubleshooting, documentation, and continuous improvement
- Partner with engineers and cross-functional colleagues through design discussions, code reviews, technical problem-solving, and knowledge sharing
This is a hybrid role based in Bengaluru with an expectation to work onsite at least 50% of the time. Diligent has offices across multiple global locations and emphasizes innovation, collaboration, and a strong sense of community.
REQUIREMENTS:
- 3–5 years of professional experience building and delivering production software in an agile environment
- Strong hands-on experience with Python and backend development, including APIs, integrations, or service-oriented applications
- Experience working with cloud platforms, preferably AWS, and familiarity with deployment or CI/CD practices
- Working knowledge of software design principles, testing, debugging, performance optimization, and secure development
- Experience with SQL databases and Git-based development workflows
- Practical understanding of AI or LLM concepts, such as generative AI, embeddings, context limits, hallucinations, or responsible AI tool use
- Clear communication and a collaborative approach to technical problem-solving and delivery
NICE-TO-HAVE:
- Experience building data-intensive applications, ingestion services, distributed systems, or workflow-based solutions
- Familiarity with containers, infrastructure as code, observability, automated quality practices, or MLOps
- Exposure to TypeScript, React, LLM integrations, prompt engineering, retrieval-augmented generation, or other modern AI application patterns
