Staff / Senior Staff Engineer, AI Agent Engineering

Equinix

Toronto

On-site

CAD 131,000 - 181,000

Full time

14 days+

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Benefits offered by this job

Healthcare coverage and core benefits
RRSP/TSFA retirement plans
Vacation and paid holidays
Employee Assistance Program

Job summary

Equinix is seeking Staff or Senior Staff Engineers to build agentic AI systems that manage the software delivery lifecycle end to end. You will design, ship, evaluate, and harden production agents trusted by colleagues across a global organization to deliver real results.

You will work on Equinix's enterprise AI platform, integrating with Jira, GitHub, and other enterprise systems while maintaining security, privacy, and compliance. The role offers high impact, deep craft, and global reach.

Qualifications

  • 6+ years (Staff) or 9+ years (Senior Staff) of professional software engineering experience, shipping production systems.
  • Hands-on experience building LLM-powered applications or agents: prompts, context, tool calling, retrieval, or multi-agent workflows.
  • Experience designing evaluations for AI systems or strong test-engineering instincts.
  • Strong proficiency in Python or TypeScript, plus API, microservices, and event-driven architecture.
  • Fluency with Git, automated testing, CI/CD, observability, and cloud platforms.
  • Sound judgment about trust vs. automation and ability to explain reasoning.

Responsibilities

  • Design, build, and ship LLM-powered agents that handle lifecycle work from intake to operations.
  • Engineer tooling for dependable agents: MCP, A2A, event orchestration, and enterprise integrations like Jira.
  • Contribute to Equinix's AI platform: gateway, orchestration, audit, and access control with privacy by design.
  • Create eval suites and guardrails, and define release gates for agent deployments.
  • Develop knowledge layers: retrieval, context standards, and reusable prompt patterns.

Skills

LLM-powered apps
Python/TypeScript
API/microservices/event-driven
Git/CI-CD/Observability
Automation vs human review judgement
Clear communication

Tools

Jira
GitHub
ServiceNow integration
MCP
A2A
LangGraph/Anthropic/OpenAI APIs

Job description

Who are we?

Equinix is the world’s digital infrastructure company®, shortening the path to connectivity to enable the innovations that enrich our work, life and planet. A place where tech thinkers and future builders turn bold ideas into breakthrough experiences, we welcome your unique perspective. Help us challenge assumptions, uncover bias, and remove barriers—because progress starts with fresh ideas. You’ll find belonging, purpose, and a team that welcomes you—because when you feel valued, you’re empowered to do your best work.

Job Summary

Most engineering roles now come with AI tools. This one comes with a mission. Equinix Incubation builds the agentic systems that run the software delivery lifecycle end to end: from intake and business case through design, code, test, release, and value tracking, with humans directing the work and owning every gate. We are hiring Staff and Senior Staff Engineers to build those agents and the platform they run on. You will not just use AI to code faster. You will design, ship, evaluate, and harden production agents that colleagues across a global organization trust with real delivery work. Your agents will write software; your engineering decides what ships.

Responsibilities
Build Production AI Agents
  • Design, build, and ship LLM-powered agents that execute real lifecycle work: intake triage, estimation, requirements, technical design, coding, testing, release, and operations
  • Engineer the scaffolding that makes agents dependable: tool use via MCP, agent-to-agent handoffs (A2A), event-driven orchestration, and deep Jira and enterprise system integration
  • Build on Equinix's enterprise AI platform: AI gateway, orchestration, audit, and access control, with security and privacy by design
Make Agents Trustworthy: Evals, Guardrails, Gates
  • Design and automate eval suites that measure agent output quality on every change, and make passing evals the release gate for agents
  • Define guardrails, human-in-the-loop approval points, review thresholds, and escalation paths, so agent autonomy is earned, not assumed
  • Instrument agent behavior end to end (quality, latency, cost, adoption), find failure patterns, and tune prompts, context, and configurations until the numbers move
Engineer Context and Knowledge
  • Build the knowledge layers agents depend on: retrieval over process libraries, decision histories, code, and delivery data
  • Establish reusable prompt patterns, context standards, and agent configurations that other teams adopt
  • Own agents through their full lifecycle: instructions, context freshness, performance monitoring, feedback, and retirement
Ship the Platform and Raise the Bar
  • Contribute to the orchestrator, persona consoles, and dashboards that keep humans in command of agent-led delivery
  • Dogfood relentlessly: use agents to build agent systems, and feed what you learn back into the platform
  • Bring strong engineering craft. The fundamentals still decide whether this works: architecture, code quality, testing, CI/CD, and cloud-native design
What Success Looks Like
  • Agents you built are doing live delivery work, with measurable cycle-time and quality gains, and humans confidently in control
  • Your eval suites are the reason people trust agent output; “passes evals” means something because you made it mean something
  • Your context patterns, guardrails, and agent standards are reused by teams you have never met
  • You can explain to an executive, in plain language, what an agent did, why, and how you know
  • The platform gets simpler, faster, and cheaper as it scales, because you treat agent cost and reliability as engineering problems
Level Expectations
  • Staff: You deliver complete agents and platform components within established patterns, own their evals and quality end to end, and are the dependable engine of your pod
  • Senior Staff: You set the patterns. You take the hardest, most ambiguous problems (orchestration, eval design, agent reliability at scale), define the standards others follow, and multiply the team
Qualifications
Required
  • 6+ years (Staff) or 9+ years (Senior Staff) of professional software engineering experience, with a record of shipping and operating production systems
  • Hands‑on experience building LLM-powered applications or agents: prompt and context engineering, tool calling, retrieval, or multi‑agent workflows
  • Experience designing evaluations for AI systems, or strong test‑engineering instincts you are eager to apply to non‑deterministic software
  • Strong proficiency in Python or TypeScript, plus solid API, microservices, and event‑driven architecture skills
  • Fluency with modern engineering practice: Git, automated testing, CI/CD, observability, and cloud platforms
  • Sound judgment about when to trust automation and when to demand human review, and the communication skills to explain that reasoning
Preferred Qualifications
  • Experience with agent frameworks and protocols such as MCP, A2A, Anthropic or OpenAI APIs, Bedrock, Vertex, or LangGraph
  • Experience building developer platforms, orchestration systems, or SDLC tooling, including Jira, GitHub, or ServiceNow integration
  • Knowledge‑engineering experience: retrieval systems, embeddings, or enterprise knowledge graphs
  • Experience taking AI features through security, privacy, and responsible AI review in an enterprise
  • Evidence of craft: open‑source contributions, technical writing, or internal platforms with devoted users
Core Competencies
Agent Engineering
  • LLM application architecture; prompt and context engineering; tool use and orchestration; multi‑agent design
Evals and Trust
  • Eval design and automation; guardrails and human‑in‑the‑loop gates; AI observability; responsible AI governance
Platform Craft
  • API and event‑driven design; CI/CD and automation; cloud‑native engineering; enterprise integration
Judgment and Impact
  • Systems thinking; pragmatic risk‑taking; mentoring and standards‑setting; clear communication
Why This Role

Incubation is a durable capability, not a project team: the team persists, and the product rotates. Agentic delivery is product one; the next incubation bets follow. You will help define how AI‑first engineering works at Equinix, with the autonomy of a startup and the reach of a global platform company. Few roles let you change how an entire organization builds software. This one exists to do exactly that.

The targeted pay range for this position in the following location is / locations are: Canada - Toronto Office TRO : 131,000 - 181,000 CAD / Annual Our pay ranges reflect the minimum and maximum target for new hire pay for the full‑time position determined by role, level, and location. The pay range shown is based on our compensation structure in place at the time of posting and may be updated periodically based on business needs. Individual pay is based on additional factors including job‑related skills, experience, and relevant education and/or training. The targeted pay range listed reflects the base pay only and does not include bonus, equity, or benefits. Employees are eligible for bonus, and equity may be offered depending on the position.

Equinix Benefits

As an employee, you become important to Equinix’s success. We ensure all your benefits are in line with our core values: competitive, inclusive, sustainable, connected and efficient. We keep them competitive within the current marketplace to ensure we’re providing you with the best package possible. So, wherever you are in your career and life, you’ll be able to enhance your experience and bring your whole self to work.

Canada Core Benefits:

  • Insurance: You may enroll in healthcare coverage that is designed to complement the provincial healthcare system, along with life, disability and optional benefit plans that are designed for you and your eligible family members.
  • Retirement: You may also enroll in Equinix‑sponsored retirement or savings plans: Defined Contribution Pension Plan (DCPP), Group Retirement Savings Plan (RRSP) and Tax‑Free Savings Plan (TSFA).
  • Vacation and Paid Holidays: Equinix offers both vacation and personal time, along with various paid holidays for you to rest and recharge. Eligibility requirements apply to some benefits. Benefits are subject to specific plan or program terms, and to change at Equinix discretion.
Employee Assistance Program

An Employee Assistance program is available to all employees.

Equinix is committed to ensuring that our employment process is open to all individuals, including those with a disability. If you are a qualified candidate and need assistance or an accommodation, please let us know by completing this form.

Equinix is an Equal Employment Opportunity and, in the U.S., an affirmative Action employer. All qualified applicants will receive consideration for employment without regard to unlawful consideration of race, color, religion, creed, national or ethnic origin, ancestry, place of birth, citizenship, sex, pregnancy / childbirth or related medical conditions, sexual orientation, gender identity or expression, marital or domestic partnership status, age, veteran or military status, physical or mental disability, medical condition, genetic information, political / organizational affiliation, status as a victim or family member of a victim of crime or abuse, or any other status protected by applicable law.

We use artificial intelligence in our hiring process. Learn more here.

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