AI Engineer

Dentsu; Pune District; Hybrid; INR 1,800,000 - 2,800,000; Full time

Benefits offered by this job

Hybrid work

Job summary

Merkle in Pune is seeking an AI Engineer to design and deploy Generative AI solutions, with emphasis on multimodal systems, agentic workflows, and knowledge-grounded AI for global brands.

The role requires hands-on experience with LLMs, gradient fine-tuning, and scalable cloud deployments. Collaboration with CX, engineering, and product teams is essential, with hybrid work and knowledge sharing across projects.

Qualifications

• Minimum 3-4 years of hands-on software development experience including building and deploying ML models into production.
• 2+ years of experience with deep learning, GenAI, or transformer-based architectures.
• Demonstrated experience building GenAI applications beyond simple RAG (e.g., agents, multimodal, fine-tuning).
• Experience integrating AI systems in enterprise-grade environments.

Responsibilities

• Build Generative AI, multimodal, and agentic AI applications using LLMs and frameworks.
• Develop scalable APIs and microservices using Python and FastAPI/Flask; containerize with Docker.
• Deploy and monitor ML/AI systems in cloud environments; collaborate with MLOps for CI/CD and monitoring.
• Work with data technologies like Spark, Hadoop, MongoDB; document experiments and results.
• Mentor engineers and contribute to reusable components and best practices.

Skills

Python

SQL

Flask

FASTAPI

Django

APIs

Docker

MLOps

PyTorch

TensorFlow

Tools

LangChain

LangGraph

LlamaIndex

AutoGen

MongoDB

Spark

Hadoop

Job description

## AI EngineerApply: DGS India - Pune - Indiqube Orchid: Full time: Posted Today: R1136619**Job Description:****AI Engineer****Role Overview**We are seeking a **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 3-4 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****AI Engineer****Transformers & Deep Learning**Understands transformers; fine-tunes small models.**Generative AI (LLMs & Multimodal)**Works with LLM APIs; simple RAG and KAG – Demonstrated by project experience**Information Retrieval & Relevance**Uses vector DBs for retrieval, knowledge graphs - – Demonstrated by project experience**Predictive Modeling**Builds and deploys ML models; applies evaluation metrics – Demonstrated by project experience**Knowledge Graphs**Integrates and retrieves from existing KGs**Conversational AI**Text-only chatbots; intent models.**Agentic Frameworks**Basic agent/tool calling.**Model Deployment**Deploys models as basic APIs.**Cloud & MLOps**Uses cloud AI services.**Big Data & Pipelines**Writes SQL/Python ETL.**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 - Indiqube Orchid**Brand:**Merkle**Time Type:**Full time**Contract Type:**Permanent