Sr AI Customer Engineer

Insight Enterprises, Inc.•Chandler, AZ

3d•$130,000 - $150,000•Hybrid

About The Position

As an Sr Customer Engineer at Insight, you will work in a fast-paced, highly-skilled team developing state-of-the-art enterprise solutions using a wide variety of artificial intelligence technologies. You will work directly with customers, engineers, sales teams and partners to deliver high quality professional service engagements to Insight’s customers. Insight is a premier partner of Google Cloud Platform (GCP), and as such, your implementations will focus on enabling customers to best utilize GCP or to demonstrate its capabilities. You will be responsible for building cloud-native artificial intelligence solutions using Google’s Gemini Enterprise Agent Platform (GEAP) and all related technologies, such as Gemini foundation models, Agent Development Kit (ADK), Agent Studio, and Vector Search. You may also be responsible for implementing domain-specific solutions such as Gemini Enterprise for Customer Experience (GECX) or AI Commerce Search. This is a hands-on, senior position that will include both architecting and implementing enterprise AI solutions. Your approach to learning new technology wil be as important as any prior knowledge. We are looking for someone with a passion for continuous learning and a knack for problem-solving, who learns quickly and always says “I’ l figure it out.” Along the way, you will get to: Implementing AI-based solutions for Insight clients across all project stages, from discovery and architecture, to development, testing and launch. Providing senior-level subject matter expertise and assistance to Insight clients and colleagues on artificial intelligence and agentic automation topics. Collaborating with client stakeholders managing the project, including other engineers and Director-level client resources. Creating technical documentation and leading solution design discussions. Assisting with technical pre-sales discussions and the review of statements of work. Your Working Style Systems-Minded Engineer: You care deeply about operational metrics like throughput, latency, and serialization boundaries, treating infrastructure stability as a critical component of model performance. Problem Solving: You possess excellent engineering instincts with a demonstrated ability to tackle complex, ambiguous data challenges across the entire machine learning and agent lifecycle. Strong Consultative Skills: You can translate complex AI and agentic concepts into actionable business strategies and solutions. Dynamic Communication: You are able to communicate complex technical concepts clearly to a broad range of internal and external stakeholders, from engineers to executive leadership.

Requirements

4+ years of relevant work experience in technical consulting, software development or cloud engineering.
1+ years of relevant work experience designing and implementing Generative AI solutions, including the use of large language models, model fine-tuning, vector embeddings, and AI application frameworks to build retrieval augmented generation (RAG) and multimodal workloads, preferably using the Gemini Enterprise Agent Platform on GCP.
AI-Assisted Engineering: Hands-on experience leveraging modern AI code generation assistants and agentic IDE tooling, specifically GitHub Copilot, Claude Code, and Google Antigravity, to accelerate technical delivery, automate boilerplate development, and optimize the broader application execution loop.
Proven experience implementing enterprise platform governance, security, and data boundaries using Agent Gateway, Agent Identity, and real-time compliance via Agent Guard / Model Armor.
Hands-on experience implementing long-term context retention and multi-turn persistence in production environments using Google's Memory Bank architecture.
Expertise in software development using Python, and familiarity with other programming languages such as JavaScript, Go or Java.
Comfortable developing frontend web frameworks for AI prototyping, such as Streamlit, Gradio or React.
Experience designing and implementing serverless and containerized solutions on common deployment runtimes, preferably Cloud Run, Google Kubernetes Engine, or Agent Runtime on Google Cloud Platform.
Experience building and maintaining high-quality, developer-friendly server-side code, such as webhooks, cloud functions, and data pipelines.
Experience with full stack development, including setting up cloud infrastructure, database services and application lifecycle management.
Ability to architect, scope, and prioritize work based on feedback from the customer or internal teams.
Experience working with analytical and transactional database systems, including SQL databases like MySQL, PostgreSQL or BigQuery.
Experience participating in sales calls and working within a business or technical consulting environment.

Nice To Haves

Exposure to containers and container orchestration, such as Docker.
Experience working with interactive development environments like JupyterLab and integrated developer tools within the Google Cloud ecosystem.
Familiarity with activating enterprise data directly where it lives using Knowledge Catalog & Smart Storage architectures to support zero-migration grounding.
Experience stress-testing and optimizing agent execution paths before production deployment using Agent Simulation & Agent Observability suites.
Exposure to model serving frameworks such as LLM and FastAPI and model training frameworks such as PyTorch and TensorFlow.
Experience in writing automated tests, including unit, integration, and acceptance tests.
Experience monitoring and scaling workloads based on latency or throughput demands.

Responsibilities

Implementing AI-based solutions for Insight clients across all project stages, from discovery and architecture, to development, testing and launch.
Providing senior-level subject matter expertise and assistance to Insight clients and colleagues on artificial intelligence and agentic automation topics.
Collaborating with client stakeholders managing the project, including other engineers and Director-level client resources.
Creating technical documentation and leading solution design discussions.
Assisting with technical pre-sales discussions and the review of statements of work.