Gen AI Engineer

Overview

Hybrid
Depends on Experience
Full Time

Skills

llm
rag
mlops

Job Details

Role: Gen AI Engineer

IP: Atos Syntel

Client Location: Toronto, Canada (Hybrid, 3 days a week)

Job Posting Description:

Seeking for a motivated GenAI Engineer to work with our Global Advanced Customer Analytics team and develop & support solutions primarily focused on contact center BOTs.

Responsibilities:

  • GenAI use cases requirements understanding working with product owners, business and

    design LLM solutions aligned with Manulife approved RAG patterns

  • Drive data requirements conversations and work with data office to get required data for the use case

  • Design efficient chunking & indexing strategies to support answer generation as per expectations

  • Develop and deploy inference APIs using frameworks like langchain and deploy to AKS or function apps

  • Capable to pick up UI work as needed to support front end integration collaborating with UI team

  • Support GenAI knowledge BOTs in production by monitoring user feedback and improve BOT response quality through enhancements as per feedback

  • Embrace best practices, processes related to MLOps, Coding best practices

  • Experience in optimizing model accuracy by efficient prompt refinements

  • Collaborate with existing members in the team, contribute to reusable GenAI code base

What we are looking for:

  • Minimum of 5 years of experience solving high-impact business problems using Machine learning & latest advancements in LLMs

  • Proven experience as a ML Engineer, with a strong focus on generative AI, prompt engineering, and RAG applications.

  • Hands-on experience using Azure AI search, Langchain, other Vector stores. Experience in Azure OpenAI. Open-source LLMs is a plus.

  • Strong software development skills with proficiency in Python, Pyspark, preferably using Databricks Azure ML. Basic knowledge of React or equivalent UI frameworks is a plus.

  • Strong experience in supporting production applications post development and continuously improve response quality to increase benefits

  • Strong collaboration skills, ability to translate sophisticated requirements into technical backlog, presentation skills, and an ability to balance a sense of urgency with shipping high-quality and pragmatic solutions.

  • Experience in productionizing code through the DevOps pipeline (git, Jenkins pipeline, code scan).

Thank you,
Jayasree
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