Software Engineer - GenAI/ Agentic AI

Chapter247; Indore District; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

Chapter247 in Indore, India is seeking an AI/ML Engineer to contribute across the full software development lifecycle. You will translate business problems into technical solutions and help design, develop, deploy, and continuously improve AI-powered features.

You will work with Python, modern backend frameworks, and state-of-the-art AI tools to build robust, secure, and scalable applications. Strong communication and collaboration with cross-functional teams are essential.

Qualifications

• Proven experience translating business problems into technical AI/ML solutions.

Responsibilities

• Contribute across the complete software development lifecycle including design, development, deployment, and continuous improvement of AI-powered features.

Skills

Backend development

AI/ML integration

NLP & LLMs

Prompt engineering

Security best practices

Communication

System design

DevOps & CI/CD

API design

Tools

FastAPI

Django REST

Flask RESTful

Pydantic

SQLAlchemy

TensorFlow

PyTorch

Hugging Face

Pinecone

Weaviate

Qdrant

FAISS

Temporal

LangGraph

CrewAI

AutoGen

Google ADK

MongoDB

PostgreSQL

MySQL

Firebase

Redis

AWS

GCP

Azure

Git

CI/CD

Docker

Pytest

Kubernetes

OCR

Job description

We are looking for an AI/ML Engineer who can contribute across the complete software development lifecycle. The ideal candidate should be capable of understanding business problems, translating requirements into technical solutions, and contributing through design, development, deployment, and continuous improvement.

Skills

• Strong hands-on experience in Python and backend frameworks such as FastAPI, Django REST, Flask RESTful, along with Pydantic, SQLAlchemy, async programming, scalable REST API design, authentication, and backend architecture patterns
• Practical experience building AI-powered applications using Generative AI, Agentic AI, LLMs, Prompt Engineering, RAG, OCR, AI agents, tool calling, memory/context management, multi-step reasoning, and autonomous workflows
• Good understanding of AI safety and security practices including prompt injection prevention, guardrails, response validation, content filtering, hallucination mitigation, secure tool execution, AI observability, and prompt/version management
• Experience with NLP, embeddings, semantic search, model training, deep learning frameworks such as TensorFlow, PyTorch, Hugging Face, and vector databases like Pinecone, Weaviate, Qdrant, ChromaDB, or FAISS
• Experience with workflow orchestration and AI agent frameworks using tools such as Temporal, LangGraph, CrewAI, AutoGen, or Google ADK.
• Hands-on experience with databases including MongoDB, PostgreSQL/MySQL, Firebase, Redis, and scalable data architecture
• Experience integrating third-party APIs, cloud services (AWS/GCP/Azure), payment/email/SMS providers, and external AI services
• Proficient with Git, CI/CD, Docker, testing frameworks like Pytest, and containerized deployment practices
• Strong understanding of secure coding practices, OWASP/API security standards, and performance optimization for scalable AI systems
• Experience using AI-assisted development tools such as Cursor, Copilot, ChatGPT, Claude, or similar tools
• Excellent verbal and written communication skills with the ability to interact effectively with clients, gather requirements, explain technical solutions, and collaborate with cross-functional teams.
• Analyse business requirements and develop backend systems and AI workflows based on implementation requirements
• Develop, maintain, and optimize AI-powered applications using LLMs, RAG pipelines, OCR systems, and Agentic AI frameworks
• Research, evaluate, and implement suitable AI/ML models, embeddings, prompts, retrieval strategies, and frameworks based on business requirements
• Conduct experiments and PoC implementations for new AI capabilities and technologies
• Implement secure, reliable, and production-ready AI systems with proper guardrails, validation mechanisms, observability, and performance optimization
• Troubleshoot technical issues, identify root causes, and provide effective solutions
• Contribute to technical discussions, coding standards, testing, and development best practices
• Integrate third-party APIs, cloud platforms, and external AI providers into the product ecosystem
• Communicate technical solutions and project updates effectively with team members and stakeholders
• Use AI-assisted engineering tools to improve development productivity and engineering workflows