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Role: Staff Software Engineer
Function: Software Engineering
Location: Bengaluru, India (Hybrid)
Type: Full-time
Compensation: Not specified
Industry: Accounting, AI/ML, B2B SaaS, Fintech
About Company
The company is building the AI brain for independent accounting firms in North America. Its platform acts as a specialized junior accountant — automating bookkeeping, document processing, and admin workflows.
Founded in 2025 and headquartered in Singapore and Bengaluru, the company is a seed-stage team of 8. It is backed by $6 million in funding and led by founders with deep AI and technology expertise.
The company is tackling a $150 billion global market that is desperately short on talent.
Position Overview
As a Staff Software Engineer, you will build the core product — AI agents, document processing pipelines, and automation workflows that take real accounting work off practitioners plates. This is a high-ownership, full-stack role where you work directly with the founders and PM, move fast with AI tools, and are fully accountable for everything you ship. No black-box vibe-coding — if you can't explain it in a code review, it doesn't go to production.
Role & Responsibilities
Must Have Criteria
Nice to Have
What We Offer
Job ID: 151139441
Skills:
Java, Failover Clustering, Cassandra, PostgreSQL, Sql, Gcp, Terraform, shell scripting, Ansible, MySQL, MongoDB, Python, AWS, Citus for PostgreSQL, Infrastructure as Code, Amazon Aurora, database sharding technologies, high-availability databases
Skills:
Aws Lambda, Cloudformation, Amazon S3, React, Typescript, Pandas, Gcp, Terraform, Aws Ec2, Amazon Rds, Azure, Python, Api Gateway, AWS, LangChain, AWS Bedrock, LangSmith, LangGraph, Next.js, Boto3
Skills:
React, Distributed Systems, Typescript, PostgreSQL, Node.js, Schema Versioning, Idempotent API Design, Event-Driven Architectures, GraphQL APIs, Object-Oriented Programming
Skills:
AWS, Rabbitmq, Java, Dynamodb, Postgres, Memcached, Kafka, Redis, MySQL, Cassandra, Sqs, Springboot, metrics, MongoDB, tracing, NoSQL systems, structured logging, SQL databases