Senior Backend Engineer Python & FastAPI (Document AI Systems):

Experience Required: 8+ Years

Location: Remote

Working Hours: Full-Time (40 Hours per Week)

Shift Timing: 5:30 PM 2:30 AM IST

Role Overview:

- We are seeking a highly experienced Senior Backend Engineer with strong expertise in Python and FastAPI to design, build, and scale a document-processing backend capable of handling large, complex PDFs and AI-driven classification workflows.

- This role emphasizes system reliability, performance, and architecture. The ideal candidate will have experience building backend services that process 200+ page documents, integrate with Large Language Models (LLMs), and support robust exception handling, auditability, and cost-efficient execution.

- A critical aspect of this role involves designing and managing document taxonomies that enable classification, multi-page document assembly, confidence scoring, and downstream compliance workflows.

Required Skills & Experience:

- 8+ years of hands-on experience with Python and FastAPI

- Proven experience in PDF processing using libraries such as PyPDF2, pdf2image, or similar tools

- Experience integrating LLM APIs for document analysis and classification (GPT-4 Vision API preferred)

- Hands-on experience with Google Cloud Platform (GCP), including:

1. Cloud Storage

2. Firestore

3. Cloud Tasks

- Strong understanding of asynchronous processing patterns, including:

1. Background workers

2. Queues

3. Retry mechanisms

- Solid systems design experience with focus on:

1. Error handling

2. Data lineage

3. Audit trails

- Experience designing or working with document taxonomies, classification schemas, or structured labeling systems for AI-driven workflows

- Hands-on experience with OCR and document-processing systems

- Experience in financial services or compliance-driven environments

Familiarity with:

1. Taxonomy versioning

2. Confidence thresholds

3. Rules-based validation frameworks

- Experience supporting loan-processing workflows by classifying, assembling, and validating borrower documents such as:

1. KYC documents

2. Income proofs

3. Bank statements

4. Agreements

- Ability to implement taxonomy-driven rules, confidence scoring, and exception handling to enable faster and auditable credit decisions.

Key Responsibilities:

- Design and develop backend services to reliably process large PDFs (200+ pages)

- Implement AI-powered document classification using defined taxonomies and confidence-scoring mechanisms

- Design, maintain, and evolve document taxonomies that drive classification, grouping, and validation logic

- Support multi-page document assembly using taxonomy-driven rules and page-level signals

- Build robust exception detection and recovery mechanisms, including:

1. Review workflows

2. Fallback paths

3. Automated error handling

- Implement comprehensive audit trails and data lineage tracking, including taxonomy versioning and classification rationale

- Optimize system architecture and performance to manage infrastructure utilization and AI inference costs

- Collaborate with cross-functional teams to deliver scalable and compliant document-processing solutions.

What We're Looking For:

- A backend engineer who thinks in terms of systems and workflows, not just APIs and endpoints

- Strong ownership mindset toward failure handling, edge cases, and long-running processes

- Ability to transform ambiguous document inputs into structured, explainable, and auditable outputs

- Comfortable working in document-heavy, AI-assisted backend environments

- Strong problem-solving skills with a focus on scalability, reliability, and maintainability