Overview:

We're hiring a senior engineer who can own problems end-to-end. Someone who's spent 10-15+ years building production software and has figured out how to use AI tooling to do it dramatically faster-not by cutting corners, but by having the judgment to know which corners don't need to exist.

This isn't a "full stack developer who uses Copilot" role. We're looking for someone who can take an ambiguous client problem, figure out what needs to be built, build it, ship it, and iterate-often in days instead of weeks. You'll work across data platforms, APIs, web applications, and increasingly, agentic systems that act autonomously on behalf of users.

You'll be one of the first hires in a pilot model we're testing: small teams, senior people, high autonomy, fast delivery. If this works, it changes how we build software across the firm. That's the bet.

What You'll Do:

Own Delivery End-to-End

• Take client problems from scoping through architecture, build, deployment, and iteration. You're not waiting for a spec.
• Deliver production-grade applications across the stack: React/TypeScript frontends, Node.js or .NET APIs, Azure cloud services, data pipelines on Databricks.
• Use AI-assisted workflows (Claude Code, Copilot, Cursor, whatever works) to compress timelines. The expectation isn't that you use specific tools-it's that you ship fast without sacrificing quality.

Design & Build Agentic Systems

• Architect and build autonomous agent systems that can reason, plan, use tools, and take actions in real-world workflows-not just chatbot wrappers.
• Design agent orchestration patterns: multi-agent coordination, human-in-the-loop checkpoints, tool use, memory, and context management.
• Build the infrastructure that supports agentic deployment: evaluation frameworks, guardrails, monitoring, and observability for systems that act on their own.
• Stay close to the frontier. The tooling is moving fast (LangGraph, CrewAI, Autogen, custom orchestration). You should have opinions about what works and what doesn't.

Multiply the Team

• Build reusable accelerators-deployment pipelines, security patterns, API scaffolding, agent frameworks-that compound across engagements.
• Raise the engineering bar on projects you touch. Code review, architecture guidance, and pattern-setting, not just your own output.
• Help less experienced engineers get better at using AI tooling effectively. Not through training decks-through working alongside them.

Prototype and Prove Things Out

• Turn business ideas into working prototypes quickly enough that stakeholders can react to real software, not slides.
• Build proof-of-concepts, internal tools, dashboards, and client-facing portals. Some will ship; some will inform decisions. Both matter.
• Generate architecture options, technical documentation, and solution accelerators using AI-then apply judgment about which option is actually right.

What You'll Bring:

• 10-15+ years of professional software engineering experience, with meaningful time spent building and shipping production systems.
• Strong full-stack fundamentals: React/TypeScript, Node.js or .NET, REST APIs, microservices, relational and document databases.
• Working experience with Azure cloud services (or equivalent depth in AWS/GCP with willingness to context-switch).
• Proven, practical use of AI development tools (Claude Code, Copilot, Cursor, or similar) in actual delivery-not just experimentation.
• Experience designing or building agentic AI systems: autonomous agents, multi-agent orchestration, tool-use architectures, or agent evaluation frameworks.
• Familiarity with data engineering concepts and platforms (Databricks, Spark, or similar) sufficient to build data-aware applications.
• Ability to work independently with minimal direction. You should be comfortable with ambiguity and confident making architectural decisions without a committee.
• Experience with agent orchestration frameworks (LangGraph, CrewAI, Autogen, Semantic Kernel, or custom implementations).
• Experience with MuleSoft or enterprise integration platforms.
• Hands-on work with LLM APIs, prompt engineering, RAG pipelines, and fine-tuning workflows.
• Familiarity with DevOps practices, CI/CD pipelines, and infrastructure-as-code.
• Experience building internal developer tools or productivity accelerators.
• Background in consulting or client-facing delivery environments
• Fluency in English
• Client-first mentality
• Intense work ethic
• Collaborative spirit and problem-solving approach

How you'll grow:

• Cross-functional skills development & custom learning pathways
• Milestone training programs aligned to career progression opportunities
• Internal mobility paths that empower growth via s-curves, individual contribution and role expansions

Perks & Benefits:

At ZS, your growth matters. We offer a comprehensive total rewards package that supports your health and well-being, financial future, time away, and professional development. With robust skills-building programs, multiple career progression paths, internal mobility, and a deeply collaborative culture, you'll have the opportunity to do meaningful work, expand your capabilities, and thrive as part of a global community. For details on total rewards in Canada, visit ZS Canada office locations | Where we work | ZS.

Hybrid working model:

We are committed to giving our employees a flexible and connected way of working. A flexible and connected ZS allows us to combine work from home and on-site presence at clients/ZS offices for the majority of our week. The magic of ZS culture and innovation thrives in both planned and spontaneous face-to-face connections.

Travel:

Travel is a requirement at ZS for client facing ZSers; business needs of your project and client are the priority. While some projects may be local, all client-facing ZSers should be prepared to travel as needed. Travel provides opportunities to strengthen client relationships, gain diverse experiences, and enhance professional growth by working in different environments and cultures.