Experience
9 - 15 yrs
Salary (CTC)
₹58.1L - ₹64.2L
Job Location
Noida, India
Vacancy
1
Designation
Staff Software Engineer
Job Type
Not specified
Job Description
Skills and Competencies
- 9+ years of software engineering experience with deep expertise in Python backend development (Lambda, API Gateway, FastAPI or similar).
- Frontend experience with React and TypeScript sufficient to review and guide UI engineers.
- Hands-on experience designing serverless architectures on AWS at production scale
- Strong knowledge of AWS Batch and Step Functions for long-running job orchestration
- Experience with AWS CDK or Terraform for infrastructure as code
- Strong data awareness — comfortable with RDS (PostgreSQL), S3, and data pipeline concepts
- Proven ability to lead technical teams and drive engineering culture
- Comfortable using AI coding tools (e.g. GitHub Copilot, Cursor, or Claude) as part of daily workflow
- Experience with LLM API integration in production applications and Familiarity with agentic workflows, MCP tools, or AI-native application patterns is a plus
- Experience with AWS Glue for ETL pipeline development is a plus
- Background in financial services or data-intensive enterprise products is a plus
- Interest in prompt engineering and designing AI-augmented developer workflows is a plus
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical discipline, or equivalent professional experience
- Own the overall technical architecture across multiple product squads
- Define and enforce engineering standards for serverless Python development on AWS
- Design AWS Batch and Step Functions orchestration patterns for long-running data pipeline jobs
- Lead cross-squad architecture decisions including API design, data modelling, and infrastructure
- Mentor and upskill Senior and Mid-level engineers across all squads
- Collaborate with the Data Engineer to define pipeline architecture and AWS Glue patterns
- Drive infrastructure-as-code practices using AWS CDK or Terraform
- Champion a design-first engineering culture — investing heavily in planning before writing code
- Encourage and model the use of AI tools for design, prototyping, and delivery acceleration
- Be the technical escalation point for complex problems across all delivery squads
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