AI Engineer

Overview

This position is hybrid in Peachtree Corners, Georgia and sits within our Product Development division, which develops, tests, and improves our software solutions in an innovative and collaborative environment.

The Opportunity

ConstructConnect is accelerating how AI is applied across our products, platforms, and engineering workflows. We are looking for an AI Engineer to design, build, and operate shared AI capabilities that other engineering teams can use to deliver secure, scalable, production-ready solutions.

In this role, you will partner with software engineering, platform engineering, data, security, and product teams to make AI easier to adopt across the organization through practical services, tooling, and repeatable implementation patterns. This is a hands-on engineering role for someone who enjoys building production systems, improving developer workflows, and helping turn promising AI concepts into reliable solutions for internal teams and customers.

Responsibilities

What You'll Be Doing

Platform & Service Development

• Design, implement, and maintain shared AI platform components such as services, SDKs, templates, workflows, and reusable libraries that software engineering teams can adopt quickly and safely.
• Contribute to engineering patterns and paved paths for AI usage, including model access, prompt handling, evaluation, observability, security, and production support.
• Partner with product, application, data, and platform teams to translate AI use cases into scalable technical solutions instead of one-off implementations.
• Build and operate reliable, cost-aware AI and ML services on cloud platforms using containerized workloads, managed services, and modern infrastructure practices.
• Build and improve internal APIs, developer tooling, and integration patterns that simplify access to AI providers, model endpoints, retrieval services, and supporting data systems.

Operations & Delivery

• Support end-to-end workflows for AI and ML use cases, including data preparation, experimentation, deployment, monitoring, and lifecycle management.
• Contribute to CI/CD practices for AI-enabled services and ML components, including automated quality checks, security controls, and release guardrails.
• Instrument AI workloads with strong observability practices, including metrics, logs, dashboards, tracing, alerting, and cost visibility.
• Troubleshoot and resolve issues related to AI and ML deployments, including latency, scalability, integration failures, reliability problems, and cloud cost concerns.

Governance & Enablement

• Partner with security, platform engineering, and architecture teams to ensure AI usage aligns with company policies for data classification, access control, privacy, and compliance.
• Evaluate emerging AI technologies, frameworks, and vendor capabilities, and share recommendations on where they may fit within ConstructConnect's engineering roadmap.
• Contribute documentation, runbooks, onboarding materials, and reference implementations that help teams adopt AI capabilities with confidence.
• This job description in no way implies that the duties listed here are the only ones that team members can be required to perform.

Qualifications

What You'll Be Doing

Required

• Bachelor's degree in Computer Science, Software Engineering, Data Science, or a related field, or equivalent practical experience.
• 5-7 years of experience in software engineering, machine learning engineering, platform engineering, or a related area building and operating production systems.
• Strong proficiency in at least one modern programming language such as Python, Go, or TypeScript, along with solid software design, debugging, and engineering fundamentals.
• Experience building and operating services on a major cloud platform, preferably Google Cloud Platform, including familiarity with compute, storage, networking, and managed services.
• Hands-on experience with containers and orchestration technologies such as Docker and Kubernetes.
• Experience with CI/CD pipelines and Git-based engineering workflows used to build, test, and deploy services and platform components.
• Familiarity with infrastructure-as-code tools such as Terraform for provisioning and managing cloud resources in a repeatable, auditable way.
• Familiarity with MLOps concepts and tools used to support model training, evaluation, deployment, and monitoring.
• Understanding of modern AI capabilities such as generative AI, embeddings, retrieval patterns, NLP, and related ML concepts, and the ability to apply them responsibly in production environments.
• Experience building APIs, services, platforms, or libraries that are consumed by other engineers, with a focus on reliability, usability, and documentation.
• Strong foundation in observability and operational excellence, including experience managing service health through metrics, logs, dashboards, and alerting.
• Experience working cross-functionally with product, data, infrastructure, platform, and security teams.
• Ability to translate technical topics into practical guidance and collaborate effectively in a distributed, remote-friendly environment.

Preferred

• Experience supporting shared AI enablement, developer productivity, or platform engineering initiatives in a multi-team SaaS environment.
• Experience with Google Cloud AI and data services such as Vertex AI, BigQuery, or related managed tooling.
• Familiarity with AI evaluation frameworks, guardrails, prompt management, model routing, and lifecycle governance.
• Experience working with vector search, retrieval-augmented generation, agentic workflows, or orchestration frameworks in production settings.
• Exposure to intelligent search, recommendation systems, NLP, or computer vision use cases.
• Background working in environments where security, governance, and operational reliability are important to AI adoption.

Physical Demands and Work Environment:

• The physical activities of this position include frequent sitting, telephone communication, and working on a computer for extended periods. Visual acuity is required to perform activities close to the eyes.

• Team members are expected to maintain a dedicated and ergonomically appropriate remote workspace.

• Team members who live within commuting distance of one of our office locations (Greater Cincinnati/Northern Kentucky or Atlanta, Georgia) are expected to work in a hybrid capacity, with regular in-office presence as determined by the team or department.

• All team members must reside and perform their work within the United States.

E-Verify Statement

ConstructConnect utilizes the E-Verify program with every potential new hire. This makes it possible for us to make certain that every employee who works for ConstructConnect is eligible to work in the United States. To learn more about E-Verify you can call 1- or visit their website. E-Verify is a registered trademark of the United States Department of Homeland Security.

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