Description

Experience: 8 -12 years

Skills: Java, Microservices, React or Type Script, AWS

• 7+ years of experience designing, architecting and developing scalable, enterprise platforms and applications
• Proficient in the following AWS services with hands on experience: EC2, Lambda, DDB and S3
• Proficient in at least one of the 2 tech stacks: TypeScript/Node.js or Java / Springboot
• Experience designing APIs and service contracts
• Familiarity with event-driven architectures
• Hands-on experience with CI/CD and IaC pipelines
• Distributed systems and Microservices
• Exposure to AWS services like Kinesis, Firehose, Cloud watch, Aurora, Step Functions, CDK, Cloud Formation, Synk

Key responsibilities

• To succeed in this role, you will be a strong engineer with hands on experience delivering large, scalable enterprise services, platforms and applications built on AWS cloud native technologies.
• You will bring experience solving complex technical challenges, architecting highly available, resilient, responsive and scalable solutions using the well established industry standards.
• In this role you will work closely with the Principle Engineers and Chief Engineer while creating, presenting, evolving, validating and executing your design.
• You will be a hands-on engineer yourself delivering key components while overlooking your team members' deliverables.
• You will possess and showcase in-depth knowledge of Database design, implementation, performance and integration with working knowledge of large scale RDBMS like Aurora and NOSQL like DDB

AI & Intelligent Automation

As part of a modern workflow platform, we are progressively introducing AI-assisted capabilities to improve productivity, decisioning, and system intelligence. As a Staff Engineer you will help shape how

• AI is applied responsibly and pragmatically across the platform and have the following responsibilities
• Design and integrate AI-assisted features into workflow and platform services, such as:
• Workflow and rules inference from structured and semi-structured inputs
• Intelligent routing, classification, and recommendations within workflows
• AI-assisted validation, schema evolution, and decision support
• Partner with platform and security teams to ensure safe, explainable, and compliant AI usage.
• Define architectural patterns for:
• Calling LLMs or AI services from long-running workflows
• Handling retries, fallbacks, and determinism in AI-driven steps
• Versioning and auditing AI-influenced decisions
• Evaluate build vs buy options for AI services (managed cloud services vs internal capabilities)

Education Qualifications:

• Bachelor’s degree in Engineering in Computer Science/Information Technology

Key Skills

Education

Any Graduate