Generative AI Engineer

Generative Engineer

Full Time

Toronto, ON (Hybrid)

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 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).