Lead Software Engineer

Publicis Groupe; India; On-site; INR 1,500,000 - 2,000,000; Full time

Benefits offered by this job

Opportunity to build next-generation AI platforms

Collaborative and innovation-driven engineering culture

Job summary

Publicis Groupe is looking for an experienced Lead AI Engineer in India with 7-12 years of experience to design and develop AI-powered applications. This role demands a strong background in building AI systems, LLM architectures, and multi-agent workflows. Key responsibilities include creating scalable AI platforms and mentoring other developers. Candidates should possess expertise in Python, containerization, and cloud platforms such as AWS and Azure, with added preference for knowledge in automotive marketing.

Qualifications

• 7-12 years of experience in AI system development.
• Strong software engineering background combined with AI expertise.
• Hands-on experience with vector databases.

Responsibilities

• Design and develop AI-native applications powered by LLMs.
• Architect AI pipelines including ingestion and embedding.
• Deploy AI services in production environments.

Skills

Building LLM-powered applications

Agentic AI architectures

Vector databases

Python

Cloud platforms (AWS, Azure)

Containerization and microservices

Embedding models and semantic search

Tools

LangChain

LangGraph

LangSmith

Job description

Overview

The Automotive Practice at Epsilon is a rapidly growing team driving growth for major players in the automotive industry - from OEMs to dealerships across North America. Part of a 1,600-member multinational team, the practice provides the automotive world’s largest service reminder platform, alongside agency services and digital media solutions. The team supports over 50% of auto dealerships in North America and maintains relationships with over 280 million customers.

We are seeking an experienced Lead AI Engineer (7-12 years) to design, build, and deploy AI-powered applications that leverage modern LLM ecosystems, Agentic AI architectures, and intelligent automation frameworks.

This role requires deep expertise in end-to-end AI system development, from solution architecture and model orchestration to production deployment and scaling. You will lead the development of Agentic AI systems, Retrieval-Augmented Generation (RAG) pipelines, and multi-agent workflows, enabling intelligent applications that interact with enterprise systems, data platforms, and external tools.

The ideal candidate combines strong software engineering background with cutting-edge AI expertise, enabling the delivery of robust, scalable, and production-grade AI solutions.

Responsibilities

• Design and develop AI-native applications powered by LLMs and agent frameworks.
• Architect end-to-end AI pipelines, including ingestion, embedding, retrieval, reasoning, and response generation.
• Define scalable AI system architectures supporting real-time and batch workloads.
• Build and orchestrate multi-agent AI systems capable of autonomous reasoning and task execution.
• Implement agent workflows using modern orchestration frameworks.
• Design tool-enabled agents that integrate with enterprise systems, APIs, and databases.
• Develop Retrieval-Augmented Generation (RAG) pipelines for enterprise knowledge systems.
• Implement vector search and semantic retrieval using modern vector databases.
• Optimize document chunking, embedding strategies, and retrieval quality.
• Build AI workflows using frameworks such as LangChain, LangGraph, LangSmith.
• Implement advanced AI workflow orchestration and stateful agent pipelines.
• Implement integrations using Model Context Protocol (MCP) to connect AI systems with enterprise tools and data sources.
• Build AI-enabled automation workflows across internal platforms.
• Deploy AI services in production environments with monitoring, scaling, and observability.
• Implement CI/CD pipelines for AI applications.
• Ensure model reliability, performance, and cost optimization.
• Implement AI observability, evaluation, and monitoring frameworks.
• Build automated pipelines for testing, validation, and continuous improvement of AI systems.
• Lead and mentor AI engineers and developers.
• Establish standard processes for AI system architecture and development.
• Evaluate emerging AI tools, frameworks, and technologies.

Qualifications

• Strong experience building LLM-powered applications.
• Deep understanding of Agentic AI architectures, Retrieval-Augmented Generation, Multi-agent systems, tool-using AI agents.
• Experience with LangChain, LangGraph, LangSmith.
• Hands‑on experience with vector databases such as Pinecone, Chroma.
• Strong software engineering skills in Python.
• Experience with containerization and microservices.
• Experience with cloud platforms (AWS, Azure).
• Experience with model deployment, inference optimization, AI service scaling, and cost optimization.
• Experience with embedding models and semantic search.
• Knowledge graph or hybrid retrieval experience is a plus.

Preferred Qualifications

• Experience in automotive marketing.
• Excellent analytical and problem‑solving skills.
• Ability to diagnose and troubleshoot problems quickly.
• Motivated to learn new applications and domains.
• Strong time‑management skills.
• Ability to take full ownership of tasks and projects.
• Experience with Agile/SCRUM process.
• Great teammate with excellent interpersonal skills.
• Excellent verbal and written communication.
• Possess Can‑Do attitude to overcome challenges.
• Self‑motivated and directed.

What We Offer

• Opportunity to build next‑generation AI platforms.
• Work with cutting‑edge Agentic AI and LLM technologies.
• High‑impact role shaping AI product strategy and architecture.
• Collaborative and innovation‑driven engineering culture.

Equal Opportunity Employer

Epsilon is an Equal Opportunity Employer. Epsilon is committed to promoting diversity, inclusion, and equal employment opportunities by using reasonable efforts to attract, recruit, engage and retain qualified individuals of all ethnicities and backgrounds, including, but not limited to, women, people of color, LGBTQ individuals, people with disabilities and any other underrepresented groups.