Agentic AI Engineer

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.

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