Sr Staff Software Engineer - AI

Sr Staff Software Engineer - AI

• JR-162380

• Hybrid

• Bengaluru

• 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 bold ideas are welcomed, human connection is valued, and everyone has the opportunity to shape their future.

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

Build the Surfaces Where Humans Command the Agents

Equinix Incubation builds the agentic systems that run the software delivery lifecycle end to end: AI agents, with humans directing the work and owning every gate. Agents without great human surfaces are just noise. This role builds the surfaces.

You will own the consoles and dashboards through which product managers approve, engineers review, security screens, and executives see value: decision inboxes, review queues, gate approvals, and live value boards. It is full-stack work where the front end is the product and the stakes are trust.

Responsibilities

Build the Consoles

• Design and build persona consoles: decision inboxes, review surfaces, approval queues, and commitment views, one clear surface per role
• Make agent work legible: what an agent did, why, with what confidence, and what needs a human, rendered so a busy owner decides in seconds
• Sweat the interaction details with UX; approval fatigue is the failure mode, and design is the defense

Build the Value and Telemetry Layer

• Build the dashboards that report cycle time, throughput, quality, adoption, agent health, and cost, live from the pipeline
• Turn telemetry into narrative: executive value boards that show committed versus realized without manual curation
• Instrument everything; the platform’s credibility rests on numbers nobody has to assemble by hand

Engineer the Full Stack

• Build the backend-for-frontend layer, APIs, and event consumers that connect consoles to the orchestrator and enterprise systems such as Jira
• Implement enterprise-grade authentication and authorization (SSO, OAuth) and respect data boundaries by design
• Ship on the approved enterprise React stack with CI/CD, automated testing, and observability as defaults

Raise the Bar

• Use agents in your own workflow and feed friction back into the platform; you are user zero
• Set frontend and BFF patterns others reuse: components, state, accessibility, performance
• Bring craft: the fundamentals still decide whether this works

What Success Looks Like

• Approvers clear their queues in minutes and trust what they see; nobody asks for a spreadsheet export as a workaround
• Executives quote your value board in their own decks
• Console patterns you built become the default for every new agent the fleet adds
• The stack stays fast, tested, and observable as surfaces multiply

Qualifications

Required Qualifications

• 6-10 years of professional software engineering experience, including ownership of large-scale production systems.
• Significant hands-on experience designing and deploying LLM-powered applications, AI agents, or intelligent automation platforms.
• Experience designing evaluation frameworks, testing strategies, and governance models for AI-enabled systems.
• Expert-level proficiency in Python or Java or TypeScript.
• Strong background in distributed systems, APIs, platform engineering, cloud-native architectures, and event-driven systems.
• Experience leading technical initiatives across teams.
• Strong communication skills with the ability to explain complex AI systems to technical and non-technical audiences.
• Proven ability to influence architecture, standards, and engineering direction.

Preferred Qualifications

• Deep experience with agent frameworks and technologies such as MCP, A2A, LangGraph, OpenAI, Anthropic, Bedrock, or Vertex AI.
• Experience building developer platforms, internal engineering products, or enterprise orchestration systems.
• Experience with RAG architectures, embeddings, vector databases, knowledge graphs, and enterprise search.
• Experience leading AI governance, privacy reviews, security reviews, and responsible AI initiatives.
• Strong record of technical leadership through open-source contributions, patents, technical pu…