AI Native Software Engineering Manager

Accenture; Toronto; On-site; CAD 100,000 - 130,000; Full time

Job summary

A leading technology consulting firm in Toronto is seeking an experienced Software Engineer to design and deploy innovative AI agents. The ideal candidate has over 10 years of experience with cloud-native systems and a solid understanding of AI platforms, alongside strong client communication skills. This position offers the opportunity to work on impactful projects in various industries and may involve travel.

Qualifications

• At least 10 years of experience in cloud-native systems.
• Minimum 1 year of experience in designing agentic solutions.
• Familiar with AI platforms such as OpenAI and Claude.

Responsibilities

• Design and engineer enterprise-ready AI agents.
• Develop integration layers across AI providers.
• Leverage cloud-native engineering practices.

Skills

Cloud-native systems

AI platforms

Python

Java

CI/CD

Client communication

Education

Bachelor's or master's degree

Tools

Kubernetes

Docker

Terraform

Job description

ARE YOU READY to step up and take your technology expertise to the next level?

There is never a typical day at Accenture, but that’s why we love it here! This is an extraordinary chance to begin a rewarding career at Accenture Technology. Immersed in a digitally compassionate and innovation-led environment, here is where you can help top clients shift to the New using leading-edge technologies on the most ground-breaking projects imaginable.

Cloud First - Software Engineering is a high performing team to join!

We focus on client adoption of disruptive technologies, technology architecture and providing specialized skills related to integration, custom software engineering, testing, application modernization, agile and more. We help our clients with the most complex projects including working in open web platforms, DevOps platforms as well as intelligent Computing and Architecture enhancement.

The Work

You’ll embed directly with clients — acting as both technologist and trusted advisor. You’ll partner with stakeholders to define use cases, rapidly prototype, and deploy agentic workflows that are robust, secure, and operational in complex enterprise domains. Often, these will be completely net new platforms and systems that need to be stitched together in our clients' environments alongside our Ecosystem partners.

Responsibilities

• Agent Architecture and Engineering: Design and engineer enterprise-ready AI agents encompassing retrieval, orchestration, policy-based routing, tool invocation, evaluation harnesses, and lifecycle observability.
• AI Platform Integration: Develop abstraction layers across AI providers (Anthropic, Google, OpenAI, etc. ) to enable seamless integration and enablement.
• Cloud-Native Engineering: Leverage containerization (Kubernetes, Docker), microservices, serverless, event-driven architectures, CI/CD, and observability to deliver scalable AI-native systems.
• Domain-Specific Workflows: Tailor and deploy agentic applications across verticals — e.g., finance, healthcare, retail — addressing domain-specific processes via intelligent automation.
• Client Engagement: Conduct design workshops, POCs, and code-with sessions to shape data-driven agent workflows with stakeholders, fostering trust and adoption.
• Measure & Improve: Define and use key metrics, test harnesses, and evaluation plans to measure agent accuracy, latency, safety, and cost effectiveness.
• Knowledge Sharing: Craft reusable patterns, documentation, and best practices to influence internal assets and client roadmaps.
• Travel may be required for this role. The amount of travel will vary from 0 to 100% depending on business need and client requirements.

Basic Qualification

• A bachelor's or master's degree in computer science, business administration, commerce or related discipline is required.
• Minimum of 10 years engineering experience with cloud-native systems (APIs, microservices, containerization, serverless).
• Minimum of 1 years of experience in designing and deploying agentic solutions (agents, orchestration, context engineering, RAG, workflows).
• Minimum of 2 years of experience with AI platforms — OpenAI, Claude, Vertex AI, plus open-source models — including building abstraction layers to manage multi-provider pipelines.
• Minimum of 10 years of experience programming in Python, Java, or equivalent; familiarity with evaluation tooling, logging, monitoring, and agent observability.
• Minimum of 10 years of experience deploying to production — CI/CD, infrastructure as code (Terraform, Helm), monitoring, and debugging.
• Minimum of 10 years of experience in client communication and collaboration, including being capable of leading technical workshops and delivering under ambiguity.

Bonus Points If

• You’ve served as an Agentic AI Engineer in an Enterprise environment
• You’ve defined or worked with enterprise-grade architectures for compound AI systems, orchestration frameworks, or agent registry/stream-based architectures.
• You understand the AI-native paradigm — blending cloud-native with generative model architectures — optimizing for performance, modularity, and efficiency.
• You’ve delivered solutions across multiple industries (e.g., finance, healthcare) by tailoring agentic workflows to industry needs.