Lead AI Engineer

Extentia Information Technology Private Limited; Pune District; Hybrid; INR 4,000,000 - 7,000,000; Full time

Job summary

Dentsu is seeking an AI Lead Engineer in Pune to drive the design and deployment of GenAI systems across multilingual, multimodal contexts. You will lead development of agentic AI workflows, knowledge-grounded retrieval, and scalable microservices, partnering with CX, data science, and engineering teams.

The ideal candidate has 5–6+ years of hands-on software and ML production experience, strong foundation in transformers, and track record of deploying enterprise-grade AI solutions in cloud

Qualifications

• Hands-on software development with ML deployment in production.
• Strong foundation in deep learning and transformer architectures.
• Experience building GenAI applications beyond basic RAG systems.
• Experience with fine-tuning LLMs and multilingual/multimodal models.
• Knowledge graph augmented retrieval and hybrid retrieval systems.

Responsibilities

• Build conversational and multimodal AI applications using LLMs and frameworks such as LangChain or similar.
• Design AI workflows with reasoning, planning, tool-use, memory, grounding, and external integrations.
• Develop KG-assisted AI systems including entity extraction and linking.
• Ensure safety and guardrails via structured evaluation.
• Transform models into scalable APIs and microservices using Python and Docker.
• Deploy and monitor ML systems on AWS/Azure/GCP; optimize cost and latency.
• Collaborate with MLOps on CI/CD, model versioning, and evaluation pipelines.
• Work with Spark, Hadoop, and MongoDB for data pipelines.
• Mentor engineers and contribute to best practices.

Skills

Python (advanced)

SQL

API development

Data engineering

Flask

FASTAPI

Django

PyTorch

TensorFlow

LLMs

RAG

Multimodal architectures

Agents

Prompt engineering

Grounding

Knowledge graphs

AWS/Azure/GCP

Apache Spark

Hadoop

MongoDB

Linear algebra

Probability/Statistics

Tools

Docker

FastAPI

Flask

Django

MongoDB

Apache Spark

Hadoop

Job description

Job Description: AI Lead Engineer Role Overview

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.

Required 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.

Experience Requirements

Minimum 5‑6 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.

Skill Category Lead AI Engineer

• Applies LoRA/QLoRA, distillation, debugging, optimization.
• Generative AI (LLMs & Multimodal) Builds tool-using pipelines, multilingual/multimodal flows.
• Information Retrieval & Relevance Implements hybrid retrieval + ranking, KG-enhanced semantic retrieval.
• Predictive Modeling Builds and tunes end-to-end ML pipelines.
• Knowledge Graphs Builds KG pipelines (entity linking, embeddings).
• Conversational AI Multi‑turn, multilingual dialogue systems with evaluation metrics.
• Agentic Frameworks Multi-step agent workflows with planning & memory.
• Model Deployment Scales services with CI/CD, monitoring, GPU/accelerator ops.
• Cloud & MLOps End-to-end model lifecycle automation.
• Big Data & Pipelines Uses Spark/Hadoop/MongoDB effectively.
• Deep Learning Understand and applied deep learning architectures – RNNs, LSTMs, Transformers.

Attitude & Mindset

• Growth-oriented, collaborative, and experimentation-driven.
• Strong problem‑solving skills with a bias toward action.
• Ability to communicate complex concepts clearly to non-technical stakeholders.

Open and flexible towards a hybrid work structure with no less than 2-days work from office – This is to ensure that the team working in the AI domain regularly connects and does knowledge exchange across projects.

Location: DGS India - Pune - Kharadi EON Free Zone Brand: Merkle Time Type: Full time Contract Type: Permanent

About dentsu

For over 120 years, innovation has been a core tenet of our offering – exploring new ways to reach, engage and nurture relationships with audiences. Together we drive a multiplier effect for clients at a global scale, through the development of Integrated Growth Solutions that are underpinned by our promise to clients: innovating to impact. Be a force for good. Sustainability is a vital part of our business and an important area of focus for our clients. We’re leading the way – helping to build a more sustainable planet. Dream loud. In this moment of transformation, we need our people to be fearless, embracing change and ambiguity, driven by the love for their work and excitement for the future. Team without limits. We create opportunities for connection and collaboration between our colleagues and clients, building a sense of belonging and having some fun along the way. Find out more about us Who we are Our Social Impact Our work