Technology Lead - GenAI Lead

Infosys; Mississauga; On-site; CAD 93,000 - 123,000; Full time

Job summary

Infosys seeks a hands-on Gen AI Lead to drive development and deployment of next-generation AI solutions using LLMs, RAG, and agentic frameworks. You will lead small teams, design scalable architectures, and mentor engineers in a fast-paced, innovative environment.

The role requires 5 years in software engineering or data science, with 2–3 years in Gen AI, strong Python, and experience with ML libraries. Relocation to Mississauga or commuting distance is expected.

Qualifications

• Bachelor’s degree required in CS/AI/ML or related field.
• 5 years of software engineering or data science experience with 2–3 years in Gen AI or LLM-based systems.
• Candidate must be located within commuting distance of Mississauga, ON or willing to relocate.
• Experience with REST API development and containerization using Docker.

Responsibilities

• Design, develop, and deploy Gen AI applications using LLMs and agentic frameworks (e.g., LangGraph, AutoGen, Crew AI).
• Fine-tune open-source and proprietary LLMs using LoRA, QLoRA, and PEFT.
• Build and optimize RAG pipelines with hybrid retrieval, semantic chunking, and vector search.
• Integrate Gen AI solutions with cloud-native services (AWS Bedrock, Azure OpenAI, GCP Vertex AI).
• Work with unstructured data (PDFs, HTML, audio, images) and multimodal models.
• Implement LLMOps practices including prompt versioning, caching, observability, and cost tracking.
• Evaluate model performance using tools like RAGAS, DeepEval, and FMeval.
• Collaborate with product managers, data engineers, and UX teams to deliver production-ready solutions.
• Mentor junior engineers and participate in code reviews and design discussions.

Skills

Python

ML/AI libraries

FAISS

Pinecone

Weaviate

Azure OpenAI

Hugging Face Transformers

LangChain

PyTorch

REST API

FastAPI

Docker

Education

Bachelor's degree in CS/AI/related field

Tools

AWS

Azure

GCP

Job description

Infosys is seeking a hands-on Gen AI / Agentic AI Lead to drive the development and deployment of next-generation AI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic AI frameworks. This role is ideal for a mid-level engineer with strong technical depth, a passion for building, and the ability to lead small teams or workstreams in a fast-paced, innovation-driven environment.

Required Qualifications

• Candidate must be located within commuting distance of Mississauga, ON (Canada) or be willing to relocate to the area.
• Bachelor’s degree or foreign equivalent required from an accredited institution. Will also consider three years of progressive experience in the specialty in lieu of every year of education.
• Candidates authorized to work for any employer in Canada without employer based visa sponsorship are welcome to apply. Infosys is unable to provide immigration sponsorship for this role at this time
• Bachelor’s degree in Computer Science, AI/ML, or related field.
• 5 years of experience in software engineering or data science, with 2–3 years in Gen AI or LLM-based systems.
• Strong Python programming skills and experience with ML/AI libraries (Hugging Face Transformers, LangChain, PyTorch).
• Hands-on experience with vector databases (FAISS, Pinecone, Weaviate, Azure AI Search).\
• Familiarity with cloud platforms and Gen AI services (AWS, Azure, GCP).
• Experience with REST API development (FastAPI, Flask) and containerization (Docker).
• Solid understanding of AI governance, model safety, and prompt engineering.

Key Responsibilities

• Design, develop, and deploy Gen AI applications using LLMs and agentic frameworks (e.g., LangGraph, AutoGen, Crew AI).
• Fine-tune open-source and proprietary LLMs using techniques like LoRA, QLoRA, and PEFT.
• Build and optimize RAG pipelines with hybrid retrieval, semantic chunking, and vector search.
• Integrate Gen AI solutions with cloud-native services (AWS Bedrock, Azure OpenAI, GCP Vertex AI).
• Work with unstructured data (PDFs, HTML, audio, images) and multimodal models.
• Implement LLMOps practices including prompt versioning, caching, observability, and cost tracking.
• Evaluate model performance using tools like RAGAS, DeepEval, and FMeval.
• Collaborate with product managers, data engineers, and UX teams to deliver production-ready solutions.
• Mentor junior engineers and contribute to code reviews, design discussions, and best practices.

Preferred Qualifications:

• Exposure to agentic workflows and autonomous agents.
• Experience with CI/CD pipelines and DevOps tools (GitHub Actions, Jenkins, Terraform).
• Familiarity with front-end integration (React, Angular, TypeScript) and GraphQL APIs.
• Knowledge of model interpretability, bias mitigation, and human-in-the-loop systems.
• Experience with multimodal models and perception systems (e.g., vision + language).

The job entails sitting as well as working at a computer for extended periods of time. Should be able to communicate by telephone, email or face-to-face.

Estimated annual compensation range for the candidate based in the below location will be:

Ontario: $ 92740 to $ 123375

About Us

Infosys is a global leader in next-generation digital services and consulting. We enable clients in more than 50 countries to navigate their digital transformation. With over four decades of experience in managing the systems and workings of global enterprises, we expertly steer our clients through their digital journey. We do it by enabling the enterprise with an AI-powered core that helps prioritize the execution of change. We also empower the business with agile digital at scale to deliver unprecedented levels of performance and customer delight. Our always-on learning agenda drives their continuous improvement through building and transferring digital skills, expertise, and ideas from our innovation ecosystem.

EEO

Infosys provides equal employment opportunities to applicants and employees without regard to race; color; sex; gender identity; sexual orientation; religious practices and observances; national origin; pregnancy, childbirth, or related medical conditions; status as a protected veteran or spouse/family member of a protected veteran; or disability.