Job Description

Backend Engineer — Agentic Finance System

Job Title: Backend Engineer — Agentic Platform

Location: India

Experience: 5–6 Years

Band: B2

Job Summary

We are looking for a skilled Backend Engineer to join our Digital and AI Solutions Engineering team, focused on building the infrastructure and services that power a next-generation agentic platform for Finance and Accounting operations. You will design and deliver the core backend components — API layers, integration connectors, event-driven pipelines, workflow state management, and data services — that enable AI agents to automate end-to-end finance processes across Purchase-to-Pay, Order-to-Cash, and Record-to-Report domains.

This is a platform engineering role. You will build reusable, multi-tenant backend services on AWS using Python and Node.js, designed so that onboarding a new client requires configuration, not custom development. You will work closely with AI engineers, integration specialists, and finance domain SMEs to ensure the platform is scalable, observable, and production-grade from day one.

Key Responsibilities

•         Design and build RESTful and event-driven backend services in Python and/or Node.js that support multi-agent orchestration, HITL workflows, and exception routing across finance processes.

•         Architect and implement the workflow state management layer — handling execution context persistence, checkpointing, idempotent retries, and safe resume for long-running finance workflows using AWS Step Functions or equivalent.

•         Implement event-driven architecture using AWS SQS, SNS, and EventBridge to decouple platform services and support asynchronous, high-throughput financial document processing.

•         Develop and maintain APIs that expose platform capabilities (exception management, approval routing, notification triggers, audit trail) to downstream consumers and front-end applications.

•         Ensure platform observability through structured logging, distributed tracing (AWS X-Ray), and CloudWatch dashboards — with alerting on SLA breaches, queue depth, and service health.

•         Collaborate with AI engineers to integrate LLM-based services and agent outputs into backend workflows, handling model responses, confidence thresholds, and fallback routing.

•         Implement security best practices — IAM role-based access, secrets management via AWS Secrets Manager, data encryption at rest and in transit, and audit logging for compliance.

Must Have Required Skills

•         5+ years of backend engineering experience with strong proficiency in Python and/or Node.js.

•         Solid experience building and deploying microservices on AWS — Lambda, ECS/Fargate, API Gateway, SQS, SNS, EventBridge, Step Functions, and RDS/Aurora.

•         Strong understanding of event-driven and async architecture patterns for distributed systems.

•         Experience designing RESTful APIs and working with message queues for decoupled, high-throughput processing.

•         Hands-on experience with relational databases (PostgreSQL, MySQL) and NoSQL stores (DynamoDB) — including schema design, indexing, and query optimisation.

•         Experience with Infrastructure as Code — AWS CDK, Terraform, or CloudFormation.

•         Solid understanding of multi-tenancy patterns — tenant isolation, per-tenant configuration, and shared service design.

•         Experience with workflow orchestration services — AWS Step Functions, Apache Airflow, or Temporal — for managing long-running, stateful processes.

•         Strong grasp of observability fundamentals — structured logging, distributed tracing, metrics, and alerting in production environments.

•         Experience with CI/CD pipelines (GitHub Actions, AWS CodePipeline, or equivalent) and container-based deployments (Docker, ECS).

Preferred Qualifications

•         Exposure to Finance and Accounting processes (P2P, O2C, R2R) or prior work in a BPO or shared services technology context.

•         Knowledge of financial compliance requirements — audit trail design, SOX control considerations, or data retention policies.

•         Familiarity with vector databases (pgvector, Pinecone) and basic understanding of how LLM-based services are consumed from backend APIs.

•         Experience with AWS Textract or similar document processing services for structured extraction from financial documents.

•         Knowledge of API security patterns — OAuth 2.0, JWT, mTLS — relevant to enterprise ERP and banking system integrations.

•         Understanding of anomaly detection pipelines in transactional data contexts.

•         Experience with human-in-the-loop (HITL) workflow patterns — task queuing, approval routing, SLA escalation, and decision capture.