Senior AI Engineer / Generative AI

Location: Toronto, ON
Work Model: Hybrid
Employment Type: Full-Time (FTE)

Required Experience

- 10+ years of software engineering experience with 5+ years in AI/ML and Generative AI
- Proven experience designing, developing, and deploying enterprise-scale GenAI solutions
- Strong expertise in LLMs, RAG, Agentic AI, Microservices, and Cloud-based AI platforms
- Experience leading technical architecture, mentoring engineering teams, and driving engineering best practices

Key Responsibilities

- Design, architect, and deploy scalable Generative AI solutions for enterprise applications.
- Build Agentic AI workflows using LLMs, orchestration frameworks, and AI tools.
- Develop end-to-end RAG (Retrieval-Augmented Generation) pipelines, semantic search, embeddings, and vector-based retrieval solutions.
- Design and develop scalable backend services, microservices, and secure REST APIs for AI applications.
- Build and integrate user-facing AI applications using contemporary frontend technologies.
- Collaborate with Data Engineering, Platform Engineering, and DevOps teams to deliver production-ready AI solutions.
- Lead model deployment, optimization, monitoring, and lifecycle management.
- Implement CI/CD pipelines, containerization, and DevOps best practices for AI applications.
- Conduct architecture reviews, mentor engineering teams, and establish coding standards and best practices.
- Translate business requirements into scalable, secure, and high-performance AI solutions.

Required Technical Skills

Programming & Full Stack

- Python (Mandatory)
- Java
- R
- SQL
- JavaScript
- ReactJS
- Node.js
- HTML5
- CSS3





Generative AI & Machine Learning

- Large Language Models (LLMs)
- Prompt Engineering
- Generative AI
- Natural Language Processing (NLP)
- Natural Language Understanding (NLU)
- TensorFlow
- PyTorch
- Keras

Agentic AI & AI Frameworks

- LangChain
- LangGraph
- Ollama
- AI Agents & Workflow Orchestration
- Tool Calling & Function Calling

RAG & Knowledge Retrieval

- Retrieval-Augmented Generation (RAG)
- Vector Databases
- Embeddings
- Semantic Search
- Vector Search
- Knowledge Retrieval

Architecture & Backend

- Microservices Architecture
- REST APIs
- API Integration
- Service-Oriented Architecture (SOA)

DevOps & Deployment

- Docker
- Kubernetes
- Git
- GitHub
- GitHub Actions
- CI/CD Pipelines
- Model Deployment & Monitoring

Databases

- SQL
- NoSQL

Preferred Qualifications

- Experience with Azure OpenAI , AWS Bedrock , or Google Vertex AI
- Experience building distributed, highly available AI systems
- Knowledge of cloud-native architectures, performance optimization, and scalable AI infrastructure
- Experience leading enterprise AI initiatives and architecture decisions

Preferred Skills

- Azure OpenAI Service
- AWS Bedrock
- Google Vertex AI
- Distributed Systems
- High Availability (HA)
- Performance Tuning
- Enterprise AI Architecture
- Agile/Scrum Delivery

Key Competencies

- Enterprise AI Solution Architecture
- Generative AI & LLM Engineering
- Agentic AI Design
- Technical Leadership & Mentoring
- Cloud-Native AI Development
- Cross-Functional Collaboration
- Problem Solving & Analytical Thinking
- Excellent Communication & Stakeholder Management

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📌 Senior AI Engineer / Generative AI | Toronto, ON - Hybrid | Fulltime FTE
🏢 AceStack
📍 Toronto