Generative AI Engineer — GCP AI Agents & BigQuery

Apex Systems

Dearborn (MI)

Hybrid

USD 69,000 - 96,000

Part time

10 days ago

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Benefits offered by this job

ESPP

401K program

HSA

Employee Assistance Program (EAP)

Certification discounts

Training programs

Job summary

Everforth Apex is seeking a hands-on Generative AI Engineer to design, build, and deploy AI-powered applications within a GCP environment. You will focus on Generative AI, agentic workflows, and enterprise data integration, delivering explainable insights to end users.

The role combines AI development with backend engineering, data integration, and cloud tech. You will work in a hybrid setup in SE Michigan, collaborating across teams, implementing robust governance, and contributing to

Qualifications

Bachelor's Degree in Computer Science, Engineering, Information Technology, Data Science, or a related field.
3–5 years of relevant software engineering, AI engineering, data engineering, or related experience.
Strong hands-on development experience with Python.
Experience developing solutions within Google Cloud Platform (GCP).
Strong software development and coding fundamentals.
Experience developing data-driven applications and integrating applications with enterprise data sources.
Ability to troubleshoot, test, and optimize complex technical solutions.

Responsibilities

Translate business requirements into AI-powered applications, algorithms, models, and automation solutions.
Design and develop intelligent applications leveraging Generative AI, natural language processing, machine learning, and intelligent automation.
Build AI agents capable of interacting with enterprise data and supporting complex analytical and investigation workflows.
Develop multi-step reasoning and tool-using agent workflows.
Integrate Google LLM capabilities with BigQuery and other GCP services.
Design mechanisms to retain relevant investigation context and intelligence across sessions.
Develop AI-powered solutions that provide clear, traceable, and explainable insights to end users.
Conduct experimentation to evaluate and improve AI solution accuracy, reliability, and effectiveness.
Develop backend services and APIs that enable integration between AI applications, enterprise data, and user-facing experiences.
Build scalable Python-based applications using frameworks such as FastAPI, Flask, or Django.
Develop services that allow AI agents to securely interact with data sources and supporting applications.
Write reusable, maintainable, and testable code following modern software engineering practices.
Build workflows that allow AI agents to generate and execute BigQuery SQL.
Monitor and optimize cloud-based AI applications for performance and reliability.
Develop AI agents capable of performing multi-step investigations and root cause analysis.
Create structured investigation memory models, with the ability to incorporate semantic approaches where appropriate.
Implement logging and traceability to support transparency across AI-driven workflows.
Establish appropriate governance mechanisms around AI-generated results and automated actions.
Ensure AI solutions provide understandable and explainable outputs for quality engineering users.
Utilize Infrastructure as Code practices with Terraform.
Support automated build, testing, and deployment through CI/CD pipelines.
Work with CI/CD technologies such as Tekton or Jenkins.
Apply Test-Driven Development (TDD), test-first development, MVP, and evolutionary design practices.
Utilize development productivity tools such as GitHub Copilot.
Work within Agile software development environments.