Lead AI Engineer

Merkle Italia; India; On-site; INR 1,800,000 - 2,800,000; Full time

Job summary

Merkle Italia is seeking a Lead Generative AI Engineer to design and deploy advanced GenAI solutions for customer engagement. You will build multimodal, knowledge-grounded AI systems and agentic workflows, collaborating with engineering, data science, and CX teams to deliver scalable production systems.

You will lead model development, fine-tuning, and deployment pipelines across cloud platforms, with emphasis on safety, evaluation, and efficiency.

Qualifications

• 5+ years of hands-on software development experience.
• Experience building GenAI applications beyond basic RAG.
• Experience with enterprise-grade AI systems.
• Hands-on with deep learning and transformer architectures.

Responsibilities

• Build multimodal and agentic AI applications using LLMs and frameworks.
• Design scalable APIs and microservices for deployment.
• Deploy and monitor ML systems on cloud platforms.
• Collaborate with CX, data science and engineering teams.
• Document models, experiments, and deployment processes.

Skills

Deep learning

Transformer models

LangChain

LangGraph

LlamaIndex

AutoGen

Reasoning

Tool use

Memory

Grounding

Knowledge graphs

Tools

PyTorch

TensorFlow

FastAPI

Flask

Django

Docker

AWS

Azure

GCP

Apache Spark

Hadoop

MongoDB

Job description

**Job Description:**We are seeking a **Lead** **Generative AI Engineer** with strong foundations in deep learning, transformer architecture, and practical experience building GenAI applications beyond basic RAG systems. The ideal candidate has hands-on experience/technical familiarity with LLM fine-tuning, multimodal models, retrieval systems, agentic frameworks, retrieval architectures, and production-grade ML deployment.This role will partner with engineering, data science, and CX teams to build intelligent agents, multimodal experiences, personalization systems, and knowledge-grounded AI solutions that power the future of customer engagement for global brands. ## **Key Responsibilities:**### **Generative AI, Multimodal Systems & Agentic Frameworks*** Build conversational and non-conversational, multimodal, and agentic AI applications using LLMs and frameworks such as LangChain, LangGraph, LlamaIndex, AutoGen, or similar.* Design AI workflows incorporating reasoning, planning, tool-use, memory, grounding, and external system integrations.* Develop Knowledge Graph (KG)-assisted AI systems, including entity extraction, linking, and KG-augmented retrieval.* Ensure safety, consistency, and hallucination-control through structured evaluation and guardrails.### **Deployment, APIs & Cloud Engineering*** Transform models into scalable APIs and microservices using Python, FastAPI/Flask, Docker.* Deploy and monitor ML/AI systems in AWS/Azure/GCP, optimizing for cost, latency, and reliability.* Collaborate with MLOps teams on CI/CD pipelines, model versioning, monitoring, and automated evaluation.* Work with big data technologies including Apache Spark, Hadoop, and NoSQL databases such as MongoDB.### **Model Development & Applied AI Engineering*** Build and optimize transformer-based and multimodal models using deep learning frameworks (e.g., PyTorch, TensorFlow).* Implement fine-tuning, alignment (RLHF/RLAIF), LoRA/QLoRA, pruning, and model evaluation pipelines.* Develop **information retrieval systems**, including hybrid dense–sparse retrieval, ranking, knowledge graphs, and relevance optimization.* Build predictive models and ML pipelines from scratch, including data preparation, feature engineering, and model selection.### **Collaboration, Documentation & Mentorship*** Work cross-functionally with CX, engineering, and product stakeholders to translate business needs into AI solutions.* Document models, experiments, evaluation frameworks, and deployment processes.* Mentor junior engineers and contribute to internal best practices, reusable components, and R&D initiatives.## **Must Have :*** **Minimum 5+ years** of hands-on software development experience including building and deploying machine learning models into production.* **2+ years of experience working with deep learning, GenAI**, or transformer-based architectures.* Demonstrated experience building GenAI applications **beyond simple RAG** (e.g., agents, multimodal, custom LLM fine-tuning).* Experience integrating AI systems in enterprise-grade environments.## **Technical Skills :*** **Programming:** Python (advanced), SQL; robust experience with API development and data engineering,* **Backend Frameworks:** Flask, FASTAPI, Django* **Machine Learning:** Predictive modelling, deep learning, optimization, embeddings, vector search, model evaluation.* **Generative AI:** LLMs, RAG, multimodal architectures, agents, prompt engineering, grounding, knowledge graphs.* **Cloud Platforms:** AWS, Azure, or GCP with hands-on experience deploying and scaling AI systems.* **Data Technologies:** Apache Spark, Hadoop, MongoDB; strong understanding of data pipelines and large-scale processing.* **Math Foundations:** Linear algebra, probability, statistics.