Junior Level GenAI Architect - LLM Engineer

* The expected base salary range for this position is $70/Hr - $80/Hr, depending on experience, skills, and internal equity.

* The Company offers a total rewards package in accordance with all applicable federal, provincial, and local laws and requirements. Benefit eligibility and offerings vary based on role, employment status, and work location.

* For contractor positions, benefits are limited to those entitlements and protections required by applicable law, which may include (as applicable) vacation pay, public holidays, leaves of absence, and other legally mandated benefits or payments.

* We may use AI-enabled and/or automated tools to support parts of our recruitment process, including application screening, interview scheduling, and candidate communications. These tools are used to enhance consistency and efficiency. All hiring decisions involve human review and are not based solely on automated processing.

Role Overview:

* We are seeking a highly skilled GenAI Architect / LLM Engineer to lead the design and implementation of enterprise-grade Generative AI solutions.

* This is not a traditional data analyst or reporting role. The position focuses on solution architecture, production deployment, and end-to-end ownership of Large Language Model (LLM) systems.

* The ideal candidate will act as a technical leader, driving GenAI strategy, building scalable systems, and mentoring engineering teams.

Key Responsibilities:

* Design and architect LLM-based solutions including RAG pipelines, AI agents, and evaluation frameworks

* Build and deploy scalable, cloud-native GenAI microservices

* Develop and optimize real-time data pipelines for AI applications (preferred over batch processing)

* Implement and manage multi-agent AI architectures

* Translate complex business requirements into production-ready AI solutions

* Conduct proof of concepts (POCs), pilot implementations, and iterative feedback cycles

* Define and enforce best practices for GenAI Ops / MLOps in production environments

* Mentor junior engineers and contribute to technical leadership within the team

Required Skills & Experience:

* Strong hands-on experience with Large Language Models (LLMs):

* OpenAI, Azure OpenAI, Anthropic, LLaMA

* Deep expertise in Retrieval-Augmented Generation (RAG):

* Vector databases, embeddings, retrieval strategies, evaluation techniques

* Strong experience with Azure Cloud (mandatory)

* Proven experience in production deployment of GenAI/ML systems (GenAI Ops / MLOps)

* Proficiency in Python and data engineering pipelines

* Strong system design and solution architecture skills

Preferred Experience:

* Experience in insurance, banking, or financial services domains

* Exposure to BI tools such as Power BI or Tableau

* Experience building multi-agent or autonomous AI systems

Red Flags:

* No experience with Azure cloud

* Only academic, experimental, or POC-level GenAI work

* Lack of production deployment experience with LLM systems

* Weak communication or inability to articulate system design decisions

Ideal Candidate Profile:

* GenAI Lead / LLM Architect / Applied AI Engineer

* Strong in system design and architecture, not just prompt engineering

* Proven ability to deliver enterprise-grade AI solutions in production

* Experienced in scalable AI engineering and cloud-native deployments