AI Engineer

About the job

Role Overview We are seeking a talented AI Engineer to join our Applied AI team in Bengaluru. This role focuses on designing, developing, and deploying production-ready AI agents and machine learning systems that power enterprise workflows. You will work at the intersection of research and engineering, turning cutting-edge AI capabilities into reliable, scalable solutions that enterprises trust with their critical operations. Key Responsibilities • AI Agent Development: Design, develop, and implement autonomous AI agents using LLMs and custom orchestration logic to solve complex enterprise workflows. • Data Pipeline Design: Build robust data pipelines for data ingestion, preprocessing, feature engineering, embedding generation, and vector database management to support AI agent operations. • Agent Orchestration & Workflow Automation: Design multi-agent systems with complex workflows, conditional logic, human-in-the-loop controls, and integration with enterprise systems (CRM, ERP, databases, APIs). • Production Deployment: Deploy AI models and agents to production environments (cloud, on-premise) using containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines. Ensure scalability and reliability. • Research & Innovation: Stay current with latest AI research, LLM advancements, agent frameworks, and emerging techniques. Prototype and evaluate new approaches to improve agent capabilities. • Cross-Functional Collaboration: Work with solutions architects, product managers, and engineers to define requirements, align on technical approaches, and deliver integrated solutions. • Code Quality & Documentation: Write clean, maintainable, and well-documented code. Conduct code reviews, create technical specifications, and maintain comprehensive documentation for AI systems. • Testing & Validation: Implement rigorous testing frameworks for AI models and agents including unit tests, integration tests, agent simulation, adversarial testing, and performance benchmarking. • Security & Compliance: Implement security best practices including data encryption, PII redaction, access controls, and compliance with enterprise security requirements (SOC2, GDPR, HIPAA). Preferred Qualifications • Experience building and deploying production agentic AI systems or multi-agent applications. • Advanced knowledge of RAG architectures, hybrid search, reranking, and context optimization techniques. • Experience with MLOps tools and practices including MLflow, Kubeflow, model versioning, A/B testing, and continuous training pipelines. • Proficiency in additional programming languages such as JavaScript/TypeScript, Java, or Go. • Experience with NLP techniques, transformer architectures, and fine-tuning LLMs for specific domains or tasks. • Understanding of reinforcement learning, particularly RLHF (Reinforcement Learning from Human Feedback) for LLM alignment. • Experience with containerization (Docker) and orchestration (Kubernetes) for ML model deployment. • Knowledge of enterprise integration patterns, APIs, microservices, and event-driven architectures. • Familiarity with BFSI domain, banking workflows, insurance processes, or other enterprise verticals. • Experience implementing AI governance, bias detection, explainability (XAI), and responsible AI practices. • Background in distributed systems, parallel processing, or high-performance computing for ML workloads.

Requirements

• Machine Learning
• Deep Learning
• LLM Application Development
• Data Engineering
• API Development

Qualifications

• Bachelor’s Degree in IT or related field
• Master’s Degree in AI (preferred)

Preferred Technologies

• Machine Learning
• Deep Learning
• LLM Application Development
• Data Engineering
• API Development

About the company

We are an enterprise AI agent platform helping companies deploy production-grade AI faster. We are growing fast across product, engineering, and go-to-market and are looking for talented engineers to join our team.