Senior Associate AI ML Engineer

Publicis Re:Sources; Bengaluru Urban; On-site; INR 3,500,000 - 5,500,000; Full time

Job summary

Publicis Re:Sources seeks an AI Senior Associate to define, govern, and scale enterprise AI using Azure AI. You will lead the design and deployment of secure, scalable AI systems spanning ML, generative AI, multimodal AI, and agent-based automation.

You will partner with business, engineering, data, and platform teams to ensure cloud-native, compliant AI solutions and contribute to MLOps practices while mentoring junior team members.

Qualifications

• 8+ years of experience in AI/ML, data platforms, or advanced analytics.
• Minimum 3+ years in Senior/Principal Engineer or equivalent role.
• Bachelor’s degree in computer science, engineering, or related field.

Responsibilities

• Define and own enterprise AI architecture roadmap with emphasis on Azure-native services.
• Design and Develop AI applications on Azure-based platforms (Data Lake, Synapse, Fabric).
• Define end-to-end model lifecycle management, MLOps and LLMOps practices.
• Ensure governance, security, and compliance across AI solutions.
• Present AI strategies and roadmaps to executive stakeholders.

Skills

Enterprise AI/ML development

System design

LLMs & embeddings

Multimodal AI

Vector search

Azure AI services

MLOps

LLMOps

Security & governance

Education

Bachelor’s degree in Computer Science, Engineering, or related field

Tools

Azure Data Lake

Azure Synapse

Azure Fabric

Vector databases

Job description

Publicis Re:Sources is at the core of Publicis Groupe, the world's largest

communications company. We are the only full-service, end-to-end shared service

organization in the industry, enabling Groupe agencies to do what they do best: innovate

and transform for their clients.

Formed in 1998 as a small team to service a few Publicis Groupe firms, Publicis

Re:Sources has grown to 6,000+ employees

in over 55 countries. We provide technology solutions and business services, including

procurement, tax, real estate, treasury and risk management, information security, and

global mobility — supporting

110,000+ employees across the Publicis Groupe network. Our people are at the center

of everything we do, bringing curiosity,

collaboration, and a commitment to excellence to their work every day.

Learn more about Publicis Re:Sources and the Publicis Groupe agencies we support at

@publicisresources.com

Role Summary

The AI Senior Associate is responsible for defining, governing, and scaling the enterprise

AI vision with a strong focus on the Microsoft Azure AI ecosystem. This role leads the

design & implementation of secure, scalable and production-grade AI systems across

machine learning, generative AI, multimodal AI, and agent-based automation.

The Senior Associate partners with business, engineering, data, and platform teams to

ensure AI solutions are cloud-native, compliant and aligned with long-term enterprise

This engineer owns model development, pipeline implementation, optimization, and

deployment, while contributing to MLOps practices and mentoring junior team

members

Key Responsibilities

1. AI Strategy & Enterprise Architecture

• Help Define and own the enterprise AI architecture roadmap with emphasis on Azurenative services, covering:


• Traditional ML and Deep Learning systems


• Large Language Models (LLMs) and multimodal AI (text, image, audio)


• Retrieval-Augmented Generation (RAG) and enterprise knowledge systems


• Recommendation and personalization engines


• Agentic AI and intelligent automation


• Responsible and compliant AI solutions


• Translate business and domain requirements into Azure-aligned AI reference


• Establish architectural standards, reusable patterns, and best practices for AI adoption across the organization.


• Design and Develop AI applications on Azure-based AI platforms, including:


• Azure Data Lake, Synapse, Fabric, or equivalent lakehouse architectures


• Vector databases (Azure AI Search, third-party integrations)


• Define scalable ingestion and processing pipelines for high-volume and real-time data.


• Help Architect integrations with enterprise systems such as:


• Data platforms and analytics tools


• Content, document, or knowledge management systems


• Event-driven architectures, APIs, and observability platforms


• Ensure solutions meet performance, availability, cost, and security objectives.

3. Model Lifecycle, MLOps & LLMOps

• Define & implement end-to-end model lifecycle management using Azure-native and


• open-source tools:


• Training, fine-tuning, evaluation, deployment, and monitoring


• Versioning, lineage, auditability, and rollback


• Drive adoption of MLOps and LLMOps best practices, including:


• CI/CD for models, prompts, and pipelines


• Monitoring for drift, bias, latency, and hallucinations


• Secure prompt management and inference governance


• Build shared AI platforms and reusable components to accelerate enterprise AI delivery.

4. Governance, Security & Responsible AI

• Ensure AI systems comply with:


• Data privacy and security regulations


• Industry and organizational compliance requirements


• Leverage Azure security and governance capabilities, including:


• Identity and access management


• Data protection and encryption


• Policy enforcement and monitoring


• Define guardrails for safe AI usage, IP protection, and risk mitigation.

5. Innovation & Technical Leadership

• Continuously evaluate emerging Azure AI capabilities and ecosystem tools.


• Drive experimentation and adoption of:


• Generative and multimodal AI


• Agent-based workflows and orchestration frameworks


• Advanced inference optimization and deployment strategies


• Act as a technical thought leader and advisor to senior leadership.


• Present AI architecture strategies, trade-offs, and roadmaps to executive stakeholders.

Required Skills & Expertise

• Deep expertise in enterprise AI/ML development and system design.


• Strong hands-on experience with:


• Large Language Models (LLMs), embeddings, fine-tuning, adapters


• Multimodal AI and RAG architectures


• Vector search and semantic retrieval


• Expert-level experience with Microsoft Azure, including Azure AI and data services.


• Proven track record implementing MLOps and LLMOps at scale.


• Strong understanding of distributed systems, cloud security, and data engineering.

Preferred Skills

• Experience with generative AI (text, image, audio, or video).


• Background in building AI platforms, Centers of Excellence (CoE), or shared services.


• Exposure to real-time or large-scale enterprise data systems.


• Familiarity with ServiceNow or Other ITSM platforms & Use cases.

Qualifications

• 8+ years of experience in AI/ML, data platforms, or advanced analytics.


• Minimum 3+ years in Senior / Principal Engineer, or equivalent role.


• Bachelor’s degree in computer science, Engineering, or related field