GenAI Architect

# GenAI Architect Design and own enterprise GenAI architectures — agents, RAG, model routing, guardrails — embedded in product platforms that ship.

Level:
Principal / Architect

Location:

Cleveland, Ohio (on-site)
Format:
Full-time## Role summary

The GenAI Architect designs, guides, and implements enterprise-grade Generative AI solutions embedded within product platforms. This role bridges AI research, engineering, and product development — ensuring GenAI capabilities are scalable, secure, and aligned with business objectives.## Location & eligibility
* ** On-site in Cleveland, Ohio** (not remote).
* Candidates must be a
** U.S. citizen
** or hold a
** valid U.S. work visa / work authorization**.## What you'll do
* Design and own the end-to-end architecture for GenAI-powered product features.
* Guide engineering teams on best practices for GenAI development and integration.
* Establish standards and patterns for prompts, agents, and inference layers.
* Ensure security, compliance, and responsible AI principles are built into every solution.## Core skillset### Generative AI & ML
* Strong understanding of Generative AI models (LLMs, multimodal models, embeddings).
* Hands-on experience with foundation models (GPT-style, Claude-style, LLaMA-style) and model adaptation techniques.
* Expertise in prompt engineering, prompt orchestration, and agent-based frameworks.
* Solid grounding in ML fundamentals: supervised/unsupervised learning, evaluation metrics, inference optimization.### AI architecture & system design
* Design scalable, modular GenAI architectures for production.
* Experience with RAG architectures, vector databases, multi-agent systems, and workflow orchestration.
* Low-latency inference, model routing, and fallback strategies.
* Event-driven, microservices, and API-first architectures.### Product engineering & integration
* Integrate GenAI into customer-facing and internal products.
* Translate product requirements into AI-driven capabilities and technical designs.
* Familiarity with A/B testing, feature flags, and iterative AI product releases.### Data & knowledge engineering
* Data pipelines, feature engineering, unstructured data processing.
* Knowledge graphs, metadata-driven architectures, document ingestion and chunking strategies.
* Data quality, provenance, and governance for AI systems.### Cloud, MLOps & platform
* Strong experience in cloud-native environments (GCP).
* MLOps: model versioning, deployment pipelines, monitoring, logging, drift detection.
* Containerization, Kubernetes, CI/CD.
* Inference optimization and cost-control strategies.### Security, privacy & responsible AI
* AI security risks (prompt injection, data leakage, model abuse).
* Guardrails, content filters, and policy enforcement.
* Responsible AI: explainability, bias mitigation, compliance.
* Familiarity with data privacy regulations (e.g. GDPR) and enterprise governance.## Required qualifications
* 8+ years in software architecture, ML engineering, or platform engineering.
* 2+ years hands-on with AI/ML systems, including Generative AI.
* Strong software engineering background (Python, Java, or similar).
* Prior work with enterprise AI governance or regulated industries.
* Familiarity with open-source AI ecosystems.
* Background in data platforms or analytics engineering.
* ** U.S. citizenship or valid U.S. work authorization (visa)** — on-site Cleveland, OH.## How we hire

Same five steps as every Solomon role: intro chat → paid take-home → build review → leadership call → offer.