Senior Manager

EXL

Generative AI Engineer responsible for building scalable AI applications. Collaborating with engineers and data scientists to deliver business value through AI solutions in Canada.

Posted 7/1/2026full-timeToronto • 🇨🇦 CanadaSenior💰 CA$110,000 - CA$130,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and building Generative and Agentic AI applications, with a strong focus on Python programming, cloud integration, and API design. Proven ability to mentor engineers and contribute to architectural decisions while fostering a culture of engineering excellence.

Highest-signal resume keywords

Python ProficiencyGenerative AI Application DevelopmentCloud Integration (GCP, AWS, Azure)API Design and DevelopmentMentorship and Coaching

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Software EngineeringModularitySystem DesignTestingPerformance OptimizationPrompt EngineeringAgent Frameworks (LangChain, LangGraph, Claude Agent SDK)Vector Databases (Pinecone, Weaviate, pgvector)Retrieval-Augmented Generation (RAG)RESTful and gRPC API Development

Soft Skills

Knowledge SharingContinuous ImprovementCollaboration

Tools & Technologies

Azure OpenAIGoogle Vertex AIAWS BedrockGoogle Cloud Platform (GCP)Amazon Web Services (AWS)Azure

Certifications & Qualifications

Bachelor’s Degree in Computer ScienceMaster’s Degree in Computer Science (Preferred)

Industry Keywords

Generative AIAgentic AIAI/ML Software ProductsCloud-Native ArchitectureDistributed Systems

Tech Stack

Tools & technologies

AWSAzureCloudDistributed SystemsGoogle Cloud PlatformGRPCPython

About the role

Key responsibilities & impact

Design, build, and ship production-grade Generative and Agentic AI applications and services for internal and external users
Develop high-quality backend services in Python, with strong software engineering rigor around testing, performance, and maintainability
Champion reusability and abstraction in everything you build by designing and building modular, well-abstracted components and libraries
Build multi-agent systems using frameworks such as LangChain, LangGraph, Claude Agent SDK and Google ADK
Integrate with leading LLM and foundation model APIs, including Azure OpenAI, Google Vertex AI, and AWS Bedrock
Design and implement Retrieval-Augmented Generation (RAG) pipelines, including document ingestion, chunking strategies, embeddings, vector search, and re-ranking
Build clean, well-tested RESTful and/or gRPC APIs with a strong focus on reliability, security, and performance
Implement observability, tracing, evaluation, guardrails for Generative and Agentic AI applications
Deploy and operate services on major cloud providers (e.g., GCP, AWS, and Azure) leveraging managed services
Contribute to platform architecture decisions and engineering best practices
Take applications from prototype through production deployment, hardening, and ongoing operation
Mentor and coach junior and mid-level engineers through code reviews, architecture discussions, and pair programming
Foster a culture of engineering excellence, knowledge sharing, and continuous improvement
Participate in technical design reviews and contribute to the professional growth of team members

Requirements

What you’ll need

10-15 years of professional software engineering experience with at least 3-5 years of experience building AI/ML software products
Bachelor’s degree in Computer Science or a related field (Master’s degree preferred)
Strong proficiency in Python, with deep software engineering fundamentals (abstraction, modularity, system design, testing, performance)
Hands-on experience building and shipping Generative and Agentic AI applications, including LLM integration, prompt engineering, and/or agentic workflows
Practical experience integrating cloud-hosted LLM APIs such as Azure OpenAI, Vertex AI, and/or AWS Bedrock
Experience with agent frameworks (e.g., LangChain, LangGraph, Google ADK, Claude Agent SDK) and vector databases (e.g., Pinecone, Weaviate, pgvector, Open Search, AlloyDB)
Hands-on experience with Google Cloud Platform (GCP), Amazon Web Services (AWS), or Azure
Strong understanding of API design, distributed systems, and cloud-native architecture
Proven track record of taking systems from design through production deployment and operation

Benefits

Comp & perks

bonus
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