Forward Deployed Engineer (AI Solutions Architect)- Cincinnati, OH

Forward Deployed Engineer (AI Solutions Architect)

Position Details

Location: Cincinnati, OH (Local Preferred; Open to Strong Remote Candidates)

Duration: Contract through February 2027 (fiscal year ends/begins), with a high likelihood of extension/conversion

About the Opportunity

Our client is expanding its AI capabilities and seeking a Forward Deployed Engineer who combines the mindset of an AI Solutions Architect with the hands-on ability to design, build, and deploy production-grade AI systems.

This role will align with one of two high-impact teams based on experience and business needs:

AI Rapid Delivery Team focused on rapidly designing, building, and deploying scalable AI solutions across enterprise workflows.

eCommerce Analytics AI Team focused on AI-powered experimentation, personalization, optimization, and real-time decisioning platforms.

As a Forward Deployed Engineer, you'll work directly with product, engineering, data, and business stakeholders to translate complex business challenges into deployable AI solutions that deliver measurable outcomes.

What You'll Do

AI Solution Architecture & Delivery

Architect, design, and deploy AI-powered applications across enterprise and customer-facing platforms.

Build and deliver production-grade solutions leveraging:

Large Language Models (LLMs)

Agent-based systems

Retrieval-Augmented Generation (RAG)

Workflow orchestration and automation

Decisioning and task-execution agents

Rapidly prototype, validate, and scale AI solutions from concept through production.

Embed AI capabilities into existing systems through APIs, microservices, and cloud-native architectures.

Develop scalable AI services and integrations that support enterprise-wide adoption.

Design human-in-the-loop workflows for high-impact AI use cases.

Collaborate closely with cross-functional stakeholders to solve ambiguous business problems.

Personalization, Experimentation & Decisioning

Build systems that support:

Personalization and audience targeting

Experimentation platforms (A/B testing, multivariate testing, bandits)

Optimization engines

Real-time decisioning experiences

Design scalable architectures that continuously improve decision quality and business outcomes.

AI Evaluation & Validation

Define and implement evaluation frameworks for:

LLM-based applications

Agent-driven workflows

RAG systems

Decisioning platforms

Create automated pipelines for:

Regression testing

Prompt evaluation

Model comparisons

Continuous validation

Measure and monitor:

Accuracy

Reliability

Latency

Cost

Business impact

Ensure production AI systems remain scalable, trustworthy, and observable.

Platform & Engineering Excellence

Build reusable frameworks, templates, and accelerators that improve AI delivery speed.

Implement monitoring, observability, and performance tracking.

Build and maintain APIs and microservices that power AI-enabled capabilities.

Support CI/CD pipelines and cloud-native deployment practices.

Contribute to scalable, maintainable engineering patterns across the organization.

Required Qualifications

7+ years of experience in Software Engineering, Solution Architecture, AI/ML Engineering, or related disciplines.

Proven experience building and deploying production-grade AI applications.

Hands-on experience integrating Large Language Models into real-world business solutions.

Strong experience with:

Prompt engineering and evaluation

API-driven architectures

Microservices development

Distributed systems

Experience designing and deploying:

Retrieval-Augmented Generation (RAG) solutions

Agent-based AI systems

Workflow orchestration platforms

Strong backend engineering experience with:

Python (FastAPI or similar)

Node.js

Experience integrating frontend applications (React preferred).

Cloud platform experience, preferably Microsoft Azure.

Ability to thrive in fast-paced, agile environments with evolving priorities.

Strong communication skills and the ability to partner directly with business stakeholders.

Preferred Qualifications

Experience with experimentation and optimization platforms.

Familiarity with:

A/B testing frameworks

Personalization platforms

Multi-armed bandit approaches

Experience with LLM orchestration frameworks such as:

LangChain

LangGraph

Experience with event-driven and asynchronous architectures.

Knowledge of AI observability, including:

Latency monitoring

Cost tracking

Token utilization analysis

Familiarity with AI governance, safety, and risk management practices.

Exposure to large-scale analytics and cloud data platforms.

Platform & DevOps Experience

Containerization using Docker.

CI/CD pipeline implementation and automation.

Kubernetes or similar orchestration platforms.

Cloud-native application deployment.

Monitoring, logging, and distributed tracing tools.

Team Environment

You'll join a highly collaborative and product-focused team made up of:

AI Engineers

Data Scientists

Software Engineers

Product and Business Partners

The culture emphasizes:

Ownership and accountability

Fast execution

Pragmatic problem-solving

Production-ready engineering

Measurable business impact

What Success Looks Like

AI solutions move from concept to production quickly and reliably.

Systems are scalable, observable, and maintainable.

AI-driven applications deliver measurable business outcomes.

Experimentation and decisioning platforms continuously improve performance.

Business teams successfully adopt and scale AI capabilities.

Reusable frameworks accelerate AI innovation across the organization.