Interested in this AI Software Engineer role at Equinix?
Apply Now →Skills & Technologies
About This Role
### Staff Software Engineer, AI/Agentic Systems
- JR\-161052
- Hybrid
- Redwood City
- Technology
- Full time
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
We are looking for a Senior Staff Engineer to lead the design, build, and adoption of AI\-powered agentic systems across our Developer Experience platform. This is a highly technical, high\-impact role at the intersection of platform engineering and applied AI — you will be responsible for the agentic execution framework that automates delivery, operations, and policy workflows for hundreds of engineers across the organization.
You will own the end\-to\-end architecture for how AI agents are built, governed, triggered, and observed on our platform — from the event\-driven backbone and human\-in\-the\-loop queues through to the agent registry and policy explainability surfaces. You will also be the internal champion for agentic development practices, partnering with engineering teams to evangelize Claude Code and AI\-assisted workflows across the organization.
Responsibilities
Agentic Execution Framework
- Architect and build the event\-driven execution framework that enables agent\-assisted workflows across delivery, operations, and policy systems (e.g., PR automation agents, CI failure triage, onboarding agents)
- Design and implement human\-in\-the\-loop approval queues, error handling, retry logic, and guardrail enforcement to ensure safe, auditable agent execution in a regulated enterprise environment
- Define the execution contract — how agents are invoked, what permissions they hold, how outcomes are recorded — across all platform integrations
Claude Code Integration \& Developer Evangelism
- Lead the platform\-native integration of Claude Code into scaffold templates, CI failure triage, PR assist workflows, and the developer portal's 'what should I work on?' agent
- Build and run an internal evangelism and adoption program for agentic development practices — demos, workshops, documentation, and a developer advocate community
- Partner with engineering teams to identify high\-value automation opportunities and convert them into governed, reusable agent workflows
Agent Registry \& Lifecycle
- Design and build a governed catalog of approved agents — metadata, capabilities, trust boundaries, versioning, and usage policies — ensuring agents are discoverable, auditable, and compliant
- Implement lifecycle management for agent versioning and permissions, including deployment pipeline integration, rollback, and decommissioning with full audit trails
Platform Security \& Governance
- Define and enforce the security posture for agent execution: scoped permissions, least\-privilege identity models, execution isolation, and immutable audit logging
- Collaborate with security, compliance, and platform governance teams to ensure all agent execution meets enterprise policy requirements
Technical
- Production experience building LLM\-powered agents — not just prototypes. Must have shipped agentic systems that use tool calling, multi\-step orchestration, and human\-in\-the\-loop patterns at scale
- Deep fluency with agentic frameworks and APIs: Claude/Bedrock APIs, Amazon Bedrock Agent Core, LangChain, n8n, or equivalent orchestration platforms
- Strong experience with event\-driven architectures as the execution backbone for agent triggers: Apache Kafka, AWS EventBridge, or equivalent
- Solid understanding of platform\-level security for agent systems: scoped IAM/RBAC, execution sandboxing, blast radius containment, and audit trail design
- Experience integrating AI tooling into CI/CD pipelines, developer portals (e.g., Backstage), and software delivery workflows
- Comfortable across the stack: Python or Go for backend agent services; familiarity with GitHub Actions, ArgoCD, and infrastructure\-as\-code tooling
- Demonstrated ability to evaluate build vs. buy tradeoffs for AI infrastructure and make architecture decisions that balance velocity with long\-term maintainability
Qualifications
- 10\+ years of software engineering experience, with at least 3 years focused on platform engineering, developer tooling, or applied AI/ML systems
- Track record of leading technically ambiguous, high\-impact projects — from architecture through to production adoption — in a large engineering organization
- Strong written and verbal communication skills; ability to translate complex technical concepts for both engineering and leadership audiences
- Experience as a technical anchor on cross\-functional teams: comfortable influencing without authority, driving alignment across security, compliance, and product stakeholders
- Prior experience building internal developer platforms, golden\-path tooling, or developer experience products is strongly preferred
The targeted pay range for this position in the following location is / locations are:
United States \- Redwood City Office GHQ : 186,000 \- 280,000 USD / 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.
Employee Assistance Program: An Employee Assistance program is available to all employees.
US Benefits: \- Insurance: You may enroll in health, life, disability and voluntary plans that are designed for you and your eligible family members. \- Retirement: You and Equinix may contribute to a retirement plan to help you plan for your financial future. \- Paid Time Off (PTO) and Paid Holidays: You will receive an accrued amount of PTO each pay period along with various paid holidays for you to rest and recharge. Eligibility requirements apply to some benefits. Benefits are subject to change and may be subject to specific plan or program terms.
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 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.
This posting is a new position within our organization.
Salary Context
This $186K-$280K range is above the 75th percentile for AI Software Engineer roles in our dataset (median: $186K across 153 roles with salary data).
Role Details
About This Role
AI Software Engineers build the applications and systems that AI models run inside. They own the API layers, data pipelines, frontend integrations, and infrastructure that turn a model into a product users interact with. Every AI company needs engineers who can build the software around the AI.
The challenge is building reliable systems around inherently unreliable components. Models are probabilistic. They'll give different answers to the same question. They hallucinate. They're slow. They're expensive. Your job is to build an application layer that handles all of this gracefully while delivering a product that users trust and enjoy.
Across the 2,799 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At Equinix, this role fits into their broader AI and engineering organization.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
What the Work Looks Like
A typical week includes: building API endpoints that serve model inference with caching and fallback logic, designing the data pipeline that feeds context to a RAG system, implementing streaming responses in the frontend, debugging a race condition in the async inference pipeline, and optimizing database queries for the vector search layer. It's full-stack engineering with AI at the center.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
Skills Required
Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.
Knowledge of vector databases, embedding APIs, and LLM integration patterns (function calling, structured outputs, retry logic) differentiates AI software engineers from general software engineers. Understanding cost optimization (caching strategies, model routing, batched inference) is valuable since inference costs can dominate application economics.
Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
Compensation Benchmarks
AI Software Engineer roles pay a median of $240,000 based on 600 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,500. Disclosed range: $186K to $280K.
Across all AI roles, the market median is $200,000. Top-quartile compensation starts at $252,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $97,760; Mid: $159,385; Senior: $227,500; Director: $242,000; VP: $250,000.
Equinix AI Hiring
Equinix has 6 open AI roles right now. They're hiring across AI Software Engineer, AI Product Manager, AI/ML Engineer. Positions span Redwood City, CA, US, Chicago, IL, US, Dallas, TX, US. Compensation range: $176K - $300K.
Location Context
Across all AI roles, 16% (460 positions) offer remote work, while 2,318 require on-site attendance. Top AI hiring metros: New York (2,241 roles, $208,300 median); San Francisco (1,822 roles, $252,000 median); Los Angeles (1,611 roles, $188,900 median).
Career Path
Common paths into AI Software Engineer roles include Software Engineer, Full-Stack Developer, Backend Engineer.
From here, career progression typically leads toward Staff Engineer, AI Architect, Engineering Manager.
If you're a software engineer, you're already 80% there. Learn the AI integration patterns: RAG, streaming inference, function calling, structured outputs. Build a project that demonstrates you can wrap an AI model in a production-quality application with proper error handling, caching, and user experience. That's the portfolio piece that gets you hired.
What to Expect in Interviews
Technical screens look like standard software engineering interviews with an AI twist. Expect system design questions about building reliable applications around probabilistic models: handling streaming responses, implementing retry logic for API failures, and designing caching strategies for LLM outputs. Coding rounds test standard algorithms plus practical integration patterns like async processing and rate limiting.
When evaluating opportunities: Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
AI Hiring Overview
The AI job market has 2,799 open positions tracked in our dataset. By seniority: 98 entry-level, 1,283 mid-level, 1,092 senior, and 326 leadership roles (Director, VP, C-Level). Remote roles make up 16% of the market (460 positions). The remaining 2,318 roles require on-site or hybrid attendance.
The market median for AI roles is $200,000. Top-quartile compensation starts at $252,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($293,500 median, 30 roles); AI Safety ($274,200 median, 43 roles); Research Engineer ($260,000 median, 387 roles).
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
The AI Job Market Today
The AI job market spans 2,799 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (1,978), AI Software Engineer (197), Data Scientist (195). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (98) are outnumbered by mid-level (1,283) and senior (1,092) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 326 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 16% of all AI roles (460 positions), with 2,318 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $200,000. Top-quartile roles start at $252,000, and the 90th percentile reaches $307,500. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $142,800. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,433 postings), Aws (840 postings), Rag (663 postings), Azure (639 postings), Gcp (537 postings), Pytorch (445 postings), Prompt Engineering (418 postings), Claude (396 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.