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GenAI Engineer

2 weeks ago

Toronto, Ontario, Canada Insight Global Full time $100,000 - $120,000 per year

GenAI Engineer

Contract
: 9 months

Hybrid
: Toronto, ON

Rate
: $70-85/hr

Required Skills & Experience

-Familiarity with frontier and open-source GenAI models (LLMs and SLMs)

-Agentic design and architecture, including integration with underlying models

-Model fine-tuning using real and synthetic data

-Experience integrating voice and chat applications to enable GenAI platforms

-Reinforcement learning techniques such as RLHF and RLAI

-Practical experience with modern GenAI design patterns (e.g., RAG, MCP)

-Understanding of vector databases, embeddings, and function/tool calls

-Knowledge of commercial GenAI offerings for SDLC enablement (generative development, AIOps)

-GenAI testing and evaluation approaches, including AI evals for performance, latency, and token consumption

Nice to Have Skills & Experience

-Experience with cloud AI services (Azure AI, AWS Bedrock, GCP Vertex AI).

-Familiarity with MLOps pipelines and deployment best practices.

-Knowledge of AI safety, ethics, and compliance frameworks.

-Exposure to multi-agent orchestration and advanced workflows.

-Proficiency in Python frameworks (LangChain, HuggingFace).

-Understanding of market trends and emerging GenAI startups.

-Experience with performance tuning for large-scale AI systems.

Job Description

Insight Global is seeking a Generative AI Engineer to join one of our large consulting clients on a 9-month contract. This individual will be responsible for designing and implementing Generative AI solutions across the entire software development lifecycle (SDLC), driving efficiency and automation end-to-end. The role requires deep technical expertise in GenAI models, architecture, and integration, as well as practical experience with modern AI design patterns and evaluation frameworks.

Key Responsibilities:

-Architect and deploy GenAI capabilities across the SDLC, enabling automation and augmentation from planning through operations.

-Design agentic systems and architectures, integrating frontier and open-source LLMs and SLMs into enterprise workflows.

-Fine-tune models using real and synthetic data for domain-specific performance.

-Integrate voice and chat applications into GenAI platforms using tools like Deepgram and Azure AI Speech.

-Apply reinforcement learning techniques (RLHF and RLAI) to improve model behavior and accuracy.

-Implement modern GenAI design patterns such as Retrieval-Augmented Generation (RAG) and Multi-Component Pipelines (MCP).

-Work with vector databases, embeddings, and function/tool calling for scalable AI solutions.

-Evaluate and recommend commercial GenAI offerings for SDLC enablement, including generative development and AIOps.

-Develop and execute GenAI testing and evaluation frameworks, measuring performance, latency, and token consumption.