Technology Analyst - Genai

Infosys is seeking a hands-on Gen AI / Agentic AI Engineer to design, develop, and deploy next-generation AI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic AI frameworks. This role is ideal for an engineer with strong technical depth, a passion for building AI-powered applications, and experience delivering production-grade GenAI solutions 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.
3–5 years of experience in software engineering, machine learning, or data science, with hands‑on experience in GenAI or LLM-based systems.
Key Qualifications
Design, develop, and deploy Gen AI applications using LLMs and agentic frameworks (e.G., LangGraph, AutoGen, Crew AI).
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.
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.
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: $ 72783 to $ 105007
About UsInfosys 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.
EEOInfosys 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.
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