AI Engineer

Equinix; Bengaluru; On-site; INR 1,800,000 - 3,200,000; Full time

Job summary

Equinix seeks a highly experienced AI platform engineer to drive the development and delivery of next-generation AI-powered platforms and agentic solutions. You will lead design/implementation of AI agents, establish governance, and collaborate with product, security, and engineering teams to deliver scalable, secure solutions that enhance customer experiences.

The ideal candidate has deep expertise in LLMs, RAG, MCP, and modern cloud-native development practices, with a hands-on leadership

Qualifications

• Bachelor’s degree in CS, SWE, or Data Science.
• 6+ years in full software development lifecycle.
• 6+ years in software design and algorithms.
• 5+ years Python or Java.
• 3+ years ML models development/deployment.
• 3+ years building LLM-powered apps or AI agents.
• Experience with prompt engineering, context engineering, tool calling, retrieval systems, multi-agent workflows.
• Experience designing APIs, microservices, distributed systems.
• Experience with MCP, A2A, and tool orchestration.
• Experience with AI platforms (Anthropic/OpenAI/Azure Bedrock Vertex AI).
• Knowledge engineering with vector DBs, embeddings, hybrid search, knowledge graphs.
• Observability, testing, CI/CD, monitoring experience.
• AWS/Azure/GC experience.
• REST API development and client SDKs.
• Strong communication; able to explain complex concepts.
• Self-motivated and able to work independently.

Responsibilities

• Design, build, deploy, and maintain LLM-powered agents and AI-driven applications
• Integrate AI capabilities into existing platforms for enhanced functionality
• Implement MCP and A2A communication patterns
• Establish automated evaluation, quality gates, benchmarking, release criteria
• Set up guardrails, human-in-the-loop, and Responsible AI governance
• Monitor/optimize agent quality, latency, observability, and costs
• Design/RAG architectures, vector DBs, and knowledge solutions
• Develop AI-enabled APIs and backend services (Python, FastAPI)
• Troubleshoot agent failures; improve prompts and context
• Build CI/CD pipelines with GitHub Actions and DevOps practices
• Collaborate with product/architecture/security/engineering teams
• Resolve client interfaces, APIs, and integration issues
• Provide hands-on leadership in architecture, design, and deployment
• Drive architectural decisions and engineering standards for AI platforms
• Define strategy with product/security/engineering leaders
• Evaluate emerging AI tech to drive innovation and continuous improvement
• Provide technical estimates, risks, and roadmap input

Skills

Analytical thinking

Communication

Adaptability to fast-paced env

Independent & team work

Self-motivated

Education

Bachelor’s degree in CS/Software Eng/Data Science

Tools

Python

Java

LangGraph

CrewAI

AutoGen

Semantic Kernel

MCP (Model Context Protocol)

A2A communication

REST APIs

FastAPI

Cloud platforms (AWS/Azure/GCP)

GitHub Actions

Containerized services

Prompt engineering

Vector databases

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.

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

Equinix is seeking a highly experienced and hands‑on engineering professional to drive the development, and delivery of next‑generation AI‑powered platforms and customer‑facing agentic solutions. This role combines software engineering excellence with deep expertise in Large Language Models (LLMs), Agentic AI, Retrieval‑Augmented Generation (RAG), Model Context Protocol (MCP), and modern cloud‑native development practices.

The ideal candidate will lead the design and implementation of AI agents, establish engineering best practices, define quality and governance frameworks, and collaborate closely with product, architecture, security, and engineering teams to deliver scalable, secure, and reliable AI solutions that enhance customer experiences and business outcomes.

Responsibilities

• Design, build, deploy, and maintain LLM‑powered agents and AI‑driven applications
• Integrate AI capabilities into existing software platforms to enhance functionality, automation, and user experience
• Implement tool integration using Model Context Protocol (MCP) and agent‑to‑agent (A2A) communication patterns
• Design and implement automated evaluation frameworks, quality gates, benchmarking processes, and release criteria for customer‑facing AI agents
• Establish guardrails, human‑in‑the‑loop approval mechanisms, escalation workflows, and Responsible AI governance controls
• Monitor and optimize agent quality, accuracy, latency, reliability, adoption, observability, and operational costs
• Design, implement, and maintain Retrieval‑Augmented Generation (RAG) architectures, vector databases, and knowledge engineering solutions
• Develop AI‑enabled APIs and backend services using technologies such as Python, FastAPI, containerized services, and REST‑based integration patterns
• Troubleshoot agent failures and continuously improve agent performance through prompt engineering, context optimization, workflow orchestration, and evaluation feedback loops
• Design, build, and manage automated CI/CD pipelines using GitHub Actions (GHA) and modern DevOps practices
• Collaborate with cross‑functional teams to gather requirements, define technical solutions, and deliver exceptional customer experiences
• Troubleshoot and resolve issues related to client interfaces, APIs, integrations, and end‑user interactions
• Provide hands‑on leadership in software architecture, design, development, automation testing, deployment, and operational support
• Drive architecture decisions and establish engineering standards for AI‑powered platforms and services
• Partner with product managers, architects, security teams, and engineering leaders to define technical strategy and execution plans
• Evaluate emerging AI technologies, frameworks, tools, and industry best practices to drive innovation and continuous improvement
• Provide technical estimates, identify risks, and contribute to roadmap planning, prioritization, and delivery execution

Qualifications

• Bachelor’s degree in computer science, Software Engineering, Data Science
• 6+ years of experience in the full software development life cycle, including coding standards, code reviews, version control, build processes, and testing
• 6+ years of experience in software design, development, and algorithm related solutions
• 5+ years of programming with Python or Java languages
• 3+ years of experience in developing, deploying or optimizing ML models
• 3+ years of hands‑on experience building LLM‑powered applications, AI assistants, or autonomous agent systems
• Experience with prompt engineering, context engineering, tool calling, retrieval systems, and multi‑agent workflows
• Solid experience designing APIs, microservices, distributed systems, and event‑driven architectures
• Experience with agent frameworks and orchestration technologies such as LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar
• Experience working with MCP (Model Context Protocol), Agent‑to‑Agent (A2A) communication, and tool orchestration frameworks
• Experience with Anthropic, OpenAI, Azure OpenAI, Amazon Bedrock, Vertex AI, or similar AI platforms
• Knowledge‑engineering experience including vector databases, embeddings, hybrid search, retrieval systems, and enterprise knowledge graphs
• Experience implementing AI observability, tracing, evaluation platforms, and cost optimization solutions
• Experience implementing automated testing, CI/CD pipelines, observability, and operational monitoring
• Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform
• Experience in REST‑based API development, API lifecycle management and/or client SDKs development
• Strong written and verbal communication skills, with the ability to explain complex concepts to non‑technical stakeholders
• Self‑motivated, with a passion for learning and staying up‑to‑date with the latest technologies in the field
• Ability to work independently and as part of a team, managing multiple tasks and projects simultaneously
• Monitor and analyze user feedback to drive continuous improvement in our applications
• Strong customer‑first mindset with a focus on platform usability and adoption
• Ability to thrive in fast‑paced, ambiguous environments

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.

This posting is for a backfill position, meaning it is to fill an existing vacancy within our organization.