Artificial Intelligence Engineer

Star Software; Bhopal; On-site; INR 1,500,000 - 2,500,000; Full time

Job summary

Star Software invites an AI Engineer to advance Intelligent Document Processing (IDP) and GenAI solutions. You will train, fine-tune, and deploy AI models, integrate with back-end services using Python/Flask, and work on OCR, layout analysis, and information extraction for enterprise documents.

You will build NLP and LLM-powered workflows, including retrieval augmented generation, AI agents, and multi-tenant architectures, with emphasis on scalable, production-ready solutions and rigorous

Qualifications

• Proven experience building AI/ML models for document processing.
• Strong knowledge of DL, CV, NLP and back-end integration.
• Experience with production-grade LLM apps and AI agents.

Responsibilities

• Train, fine-tune, and evaluate DL models for IDP and document processing.
• Develop object detection, OCR, and information extraction pipelines.
• Build NLP pipelines including NER and text-to-SQL components.
• Optimize model latency and scalability in production.
• Create reusable AI pipelines for enterprise document workflows.

Skills

Python

Deep Learning

Computer Vision

NLP

Generative AI

OCR/Document AI

PyTorch/TensorFlow

RAG/Vector retrieval

SQL/PostgreSQL

MLOps (Weights & Biases)

Tools

Flask

pgvector

vector databases

OpenAI API

Redis

PostgreSQL

Job description

Company Description

Star Software provides end-to-end automated workflows for Finance operations, including Procure-to-Pay and Order-to-Cash, as well as the management of complex documents such as Certificates of Analysis and Material Test Certificates. The company's solutions are powered by Intelligent Document Processing, Artificial Intelligence, Optical Character Recognition, and Robotic Process Automation to deliver high accuracy, efficiency, and smooth integration with existing enterprise systems. Star Software focuses on continuous improvement and user-centric innovation, helping organizations streamline critical processes and reduce manual effort. Team members contribute to technology that enables clients to concentrate on strategic initiatives and drive business success, while being part of a growing "Constellation of Automation."

Role Description

We are looking for an AI Engineer to build next-generation Intelligent Document Processing (IDP) and Generative AI solutions. The ideal candidate should have strong experience in Deep Learning, Computer Vision, NLP, and backend development, with the ability to train, fine-tune, evaluate, and deploy AI models as well as build production-ready AI applications.

You will work on OCR, Document AI, object detection, information extraction, Retrieval-Augmented Generation (RAG), AI agents, and enterprise AI applications.

Responsibilities

• Train, fine-tune, and evaluate Deep Learning models for Document AI applications.
• Develop object detection, document layout analysis, OCR, and information extraction models.
• Build Named Entity Recognition (NER) and NLP pipelines.
• Optimize model accuracy, latency, and inference performance.
• Perform hyperparameter tuning and experiment tracking.
• Build reusable AI pipelines for document processing.

LLM & Generative AI

• Build AI chatbots and enterprise GenAI applications.
• Design AI agents and multi-step workflows.
• Build Text-to-SQL solutions.
• Implement prompt engineering strategies.
• Work with embeddings, semantic search, and vector retrieval.
• Design conversation memory and context management.
• Integrate OpenAI APIs and other LLM providers.
• Develop scalable backend services using Python and Flask.
• Work with PostgreSQL, Redis, and vector databases.
• Build multi-tenant AI applications.
• Optimize SQL queries and backend performance.

Deployment & Quality

• Write unit and integration tests using PyTest.
• Monitor model performance and production systems.
• Debug AI models and backend applications.
• Collaborate with product and engineering teams to deliver production-ready AI solutions.

Required Skills

Programming

• Strong problem-solving and logical reasoning
• Data Structures & Algorithms
• Hugging Face Transformers
• Experiment Tracking

Computer Vision

• Layout Analysis

NLP

• Named Entity Recognition (NER)

Generative AI

• Prompt Engineering
• pgvector (or similar vector databases)
• Structured Outputs
• Complex SQL Query Optimization
• Multi-tenant Architecture

Data Processing

• Pandas

MLOps & Monitoring

• Weights & Biases (W&B)
• Experiment Tracking
• Performance Monitoring
• Benchmarking

Nice to Have

• Triton Inference Server

Preferred Qualifications

• Experience training custom object detection and OCR models.
• Experience building production LLM applications and AI agents.
• Strong understanding of model evaluation metrics, dataset creation, and production deployment.