AI Engineering & Enterprise Platforms

Experience: 1-2 Years

Employment Type: Full Time

Department: AI Engineering & Enterprise Platforms

Location: Bengaluru / Hybrid

Organization Overview

We are building next-generation AI-powered enterprise applications focused on compliance, audit automation, financial services, risk management, digital trust, intelligent decision support, and business process automation. Our vision is to develop Virtual AI Professionals, AI Audit Agents, AI Compliance Assistants, and autonomous AI systems that augment human expertise and accelerate delivery through responsible adoption of AI technologies.

About the Role

We are seeking highly motivated AI professionals with 1-2 years of experience to join our growing AI Engineering organization. Candidates will work on cutting-edge initiatives involving Generative AI, Agentic AI, Machine Learning, Data Science, Computer Vision, AI Engineering, MLOps, LLMOps, cloud-native AI platforms, and enterprise automation solutions.

Project Exposure

Generative AI and Large Language Models (LLMs); Agentic AI and Autonomous Workflows; Virtual AI Assistants and Custom AI Agents; AI-powered Audit and Compliance Solutions; Financial Intelligence Applications; RAG Solutions; AI Search Platforms; Predictive Analytics; Intelligent Document Processing; OCR; Conversational AI; WhatsApp Business API Integrations; FastAPI Microservices; Azure AI Services; Vector Databases; MLOps and LLMOps.

Key Responsibilities

• Develop AI, ML and GenAI applications
• Build RAG, AI Agent and intelligent automation solutions
• Design APIs and microservices using Python and FastAPI
• Integrate AI services with enterprise applications and WhatsApp Business APIs
• Develop data pipelines, model evaluation and analytics workflows
• Collaborate with architects and cross-functional teams
• Ensure security, scalability and performance of AI solutions

AI Engineering Expectations

• Production-ready AI application development
• Prompt engineering and LLM orchestration
• Vector search and retrieval systems
• Cloud-native deployment and API design
• Enterprise integration capabilities

MLOps & LLMOps Expectations

• CI/CD for AI solutions
• Model deployment and monitoring
• MLflow and experiment tracking
• Observability and performance monitoring
• Model governance and lifecycle management

Technical Skills

• Python
• FastAPI
• Pandas
• NumPy
• Scikit-learn
• PyTorch or TensorFlow
• LangChain / LangGraph / Semantic Kernel
• Azure AI Services
• Docker
• GitHub Actions
• Azure DevOps
• PostgreSQL
• Qdrant/FAISS/Pinecone
• REST APIs

Preferred Qualifications

• Experience with GenAI and RAG
• Knowledge of AML, Audit, Compliance or Financial domains
• Exposure to Computer Vision or NLP
• Azure cloud experience
• Strong communication and analytical skills