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Bengaluru, Karnataka, India
Hybrid
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 bold ideas are welcomed, human connection is valued, and everyone has the opportunity to shape their future.
Job Summary
Build the Agents That Build Our Software
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 cloudnative 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 Qualifications
3+ years 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.
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.
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