Senior AI Engineer

Position Overview

We are seeking a Senior AI Engineer to join a team responsible for developing the foundational platforms and services that enable agentic commerce and next-generation AI-powered digital experiences.

In this role, you will work at the intersection of software engineering, cloud-native architecture, API platform development, and AI application engineering. You will design and build scalable APIs, Model Context Protocol (MCP) servers, AI agents, enterprise integrations, and backend services that connect AI ecosystems with internal and external partner platforms.

This is an exciting opportunity to help define the future of enterprise AI and digital commerce while working with emerging technologies and AI interoperability standards.

Key Responsibilities

API & Platform Engineering

• Design, develop, and maintain scalable APIs supporting AI-powered customer experiences and agentic commerce platforms.

• Build and enhance MCP (Model Context Protocol) servers that expose tools, resources, and APIs to AI agents.

• Develop integrations with internal enterprise systems and external partner platforms.

• Build production-ready backend services using Golang, Python, and cloud-native technologies.

• Define and implement API contracts using OpenAPI/Swagger specifications and API-first design principles.

• Support API governance, lifecycle management, versioning, documentation, and developer enablement initiatives.

• Design highly available, resilient, secure, and observable distributed services.

AI & Agent Engineering

• Design and develop AI agents, agentic applications, and AI-enabled workflows using modern orchestration frameworks.

• Build integrations between AI platforms, enterprise applications, APIs, and partner ecosystems.

• Develop and support Retrieval-Augmented Generation (RAG) solutions and AI-powered applications.

• Contribute to architecture decisions involving MCP, Agent-to-Agent (A2A), UCP, ACP, and other emerging AI interoperability protocols.

• Evaluate and implement multi-agent orchestration patterns.

• Support proof-of-concepts, rapid experimentation, and productionization of emerging AI technologies.

• Help establish engineering standards and best practices for enterprise AI applications.

• Balance AI model performance, latency, scalability, reliability, security, and cost.

Collaboration & Technical Leadership

• Partner with Product, Security, Architecture, Platform, and Engineering teams to deliver scalable enterprise solutions.

• Drive engineering best practices around authentication, authorization, security, observability, resiliency, and performance.

• Participate in architecture reviews, technical planning, solution design, and engineering discussions.

• Provide technical guidance and mentorship to other engineers.

• Leverage AI-assisted development tools while maintaining strong software engineering, testing, security, and code-quality standards.

• Contribute to continuous improvement and overall engineering excellence.

Required Qualifications

• 5+ years of professional software engineering experience building APIs, backend platforms, microservices, and distributed systems.

• Strong hands-on experience designing and developing RESTful APIs.

• Professional software development experience with:

  • Golang

  • Python

• Strong understanding of OpenAPI specifications, Swagger, and API-first design principles.

• Hands-on experience implementing modern identity and security technologies, including:

  • OAuth 2.0

  • OpenID Connect (OIDC)

  • Zero Trust security principles

  • Modern authentication and authorization models

• Experience designing and building microservices and distributed applications in cloud-native environments.

• Experience deploying and operating applications in Microsoft Azure and/or Google Cloud Platform (Google Cloud Platform).

• Hands-on experience with Kubernetes-based environments.

• Strong understanding of software architecture, API integration patterns, distributed systems, and API lifecycle management.

• Experience with CI/CD pipelines, automation, and modern DevOps practices.

• Experience using AI-assisted software development tools such as:

  • GitHub Copilot

  • Claude Code

  • OpenAI Codex

  • Similar AI development tools

• Strong problem-solving, analytical, communication, and collaboration skills.

Preferred Qualifications

AI & Agent Engineering

• Hands-on experience building MCP (Model Context Protocol) servers, preferably in production environments.

• Experience developing AI agents and agentic workflows.

• Experience with LangChain and LangGraph.

• Experience designing and implementing Retrieval-Augmented Generation (RAG) solutions.

• Knowledge of multi-agent orchestration architectures.

• Familiarity with AI interoperability standards and protocols such as:

  • MCP

  • A2A

  • ACP

  • UCP

• Understanding of how traditional APIs are exposed as tools and resources for AI agents and AI systems.

• Experience evaluating trade-offs across AI model performance, latency, reliability, scalability, and cost.

• Strong engineering judgment when leveraging AI coding assistants and generative AI technologies.

Commerce & Integration Platforms

• Experience with digital commerce, personalization, recommendation systems, conversational AI, or search platforms.

• Experience designing and building partner-facing APIs and integrations.

• Experience working with complex internal and external partner ecosystems.

• Familiarity with API development and developer-experience tools such as Postman.

Cloud & Platform Engineering

Experience working with technologies and architectural patterns including:

• Kubernetes

• Microsoft Azure

• Google Cloud Platform (Google Cloud Platform)

• CI/CD platforms and automation

• Microservices architecture

• Distributed systems

• Cloud-native application architecture

• API management and governance

• Observability and monitoring

Technical Environment

The technology environment includes:

• Golang

• Python

• REST APIs

• OpenAPI / Swagger

• Model Context Protocol (MCP)

• AI Agents / Agentic Workflows

• LangChain / LangGraph

• RAG

• OAuth 2.0

• OpenID Connect (OIDC)

• Zero Trust Architecture

• API Lifecycle Management

• Microservices

• Kubernetes

• Microsoft Azure

• Google Cloud Platform (Google Cloud Platform)

• CI/CD Pipelines

• Distributed Systems

• AI-Assisted Development Tools

Ideal Candidate Background

Candidates may currently hold or have previously held titles such as:

• Senior Backend Engineer

• Staff Backend Engineer

• Senior AI Engineer

• AI Platform Engineer

• AI Application Engineer

• API Engineer

• Platform Engineer

• Senior Software Engineer

• Software Engineer with AI application development experience

What We''re Looking For

The ideal candidate combines strong traditional backend engineering expertise with modern AI application development experience. You should be comfortable moving seamlessly between building enterprise-grade APIs and distributed systems and developing AI agents, MCP servers, and AI-enabled applications.

You will bring strong engineering judgment and the ability to balance innovation, scalability, maintainability, performance, and enterprise-grade security while helping build the next generation of AI-powered commerce platforms.