AI Engineer (Generative AI / MLOps / AI Agents)

Job Title: AI/ML Engineer – Generative AI & LLM

Job Summary

We are seeking a skilled AI/ML Engineer with expertise in Generative AI, Large Language Models (LLMs), and agent-based systems. The ideal candidate will design, develop, and deploy scalable AI solutions, leveraging modern frameworks and cloud-based MLOps practices to deliver production-grade systems. This role involves close collaboration with cross-functional teams to translate business requirements into intelligent, reliable AI applications.

Key Responsibilities

Generative AI & LLM Development

• Design, fine-tune, and deploy LLM-based solutions for enterprise use cases such as document intelligence, summarization, and conversational AI.
• Build Retrieval-Augmented Generation (RAG) pipelines using vector databases to enhance response accuracy and contextual grounding.
• Develop prompt engineering strategies and evaluation frameworks to ensure output quality, consistency, and safety.
• Integrate LLMs with enterprise systems using frameworks like LangChain, LlamaIndex, or similar tools.
• Evaluate and benchmark different foundation models to select optimal solutions for business needs.

AI Agents & Intelligent Automation

• Architect and implement AI agents capable of multi-step reasoning and task execution.
• Develop agentic workflows using modern design patterns for complex, multi-turn interactions.
• Implement human-in-the-loop mechanisms to ensure compliance, reliability, and risk control.
• Integrate AI agents with APIs, enterprise platforms, and orchestration tools.
• Establish guardrails, monitoring, and audit logging for responsible AI usage.

MLOps & Deployment

• Build and maintain end-to-end MLOps pipelines including training, validation, deployment, and monitoring.
• Implement CI/CD pipelines for machine learning models to enable continuous delivery.
• Deploy models as scalable APIs or batch services using cloud-native platforms.
• Monitor model performance for drift, degradation, and anomalies in production.
• Maintain model governance, versioning, and lineage tracking for auditability.

Collaboration & Delivery

• Work with business stakeholders to translate requirements into AI-driven solutions.
• Participate in Agile/Scrum development processes and contribute to sprint deliverables.
• Create technical documentation including solution designs, APIs, and operational guides.
• Mentor junior team members and contribute to best practices in AI engineering.