Solutions Architect - AI

Five Below Inc; Philadelphia (Philadelphia County); On-site; USD 180,000 - 240,000; Full time

Job summary

Five Below is seeking a seasoned AI Architecture & Strategy leader to own the enterprise AI architecture across retail domains, including merchandising, supply chain, stores, marketing, and e-commerce. You will translate business problems into scalable AI blueprints and champion open-source tooling and governance.

The role requires hands-on design of end‑to‑end AI systems, strong communication with technical and business stakeholders, and partnership with product and security teams to embed AI

Qualifications

• 9+ years of experience in software, data, or AI engineering with 5+ years in AI/ML architecture roles.
• Proven experience delivering production AI solutions in retail/e-commerce or consumer-facing industries.
• Deep hands-on expertise with open-source AI/ML ecosystem and cloud platforms.

Responsibilities

• Define enterprise AI architecture for retail use cases and reference architectures.
• Lead open-source AI framework selection, governance, and deployment patterns.
• Architect end-to-end AI solutions across data ingestion, feature engineering, model training, inference, and integration.
• Establish AI observability and security standards, with MLOps coordination.
• Define productivity tooling adoption and governance for AI across teams.
• Collaborate with business and product leaders to prioritize high-impact AI opportunities.

Skills

Communication skills

Python

ML frameworks

Retail/consumer experience

Open‑source ecosystem

Architectural design

Cloud platforms

Tools

Hugging Face

LangChain

LlamaIndex

MLflow

Ray

Feast

Evidently

Databricks

Snowflake

vLLM

Ollama

llama.cpp

OpenLLM

Job description

Key Responsibilities

• AI Architecture & Strategy: Define and own the enterprise AI architecture for retail use cases, aligning with business priorities and technology strategy. Develop reference architectures, patterns, and standards for AI/ML and Generative AI solutions, with an emphasis on open-source-first design principles. Translate retail business problems — across merchandising, supply chain, stores, marketing, and e-commerce — into scalable AI solution blueprints. Partner with business and product leaders to identify and prioritize high-impact AI opportunities. Champion open-source AI frameworks and tooling (e.g., Hugging Face, LangChain, LlamaIndex, Ray, MLflow, Feast) as the default approach before evaluating commercial alternatives.
• Open-Source AI Architecture: Lead the selection, evaluation, and integration of open-source AI and ML frameworks into Company’s enterprise architecture. Design reusable patterns for open-source LLM deployment, fine-tuning, and serving (e.g., vLLM, Ollama, llama.cpp, OpenLLM). Establish governance standards for open-source model usage, including licensing review, security scanning, and model provenance tracking. Build internal capability around open-source foundations to reduce vendor lock-in and accelerate experimentation velocity. Evaluate and adopt emerging open-source agentic frameworks (e.g., AutoGen, CrewAI, LangGraph) for retail automation use cases.
• AI Solutioning & Design Architect: Architect end-to-end AI solutions, including data ingestion, feature engineering, model training, inference, and system integration. Design AI systems for core retail domains such as: Search, recommendations, and personalization. Demand forecasting, inventory optimization, replenishment, and allocation. Pricing and markdown optimization. AI assistants and copilots for store, merchandising, and supply-chain teams. Define integration patterns between AI services and retail platforms (POS, OMS, WMS, CRM, e-commerce). Lead architectural reviews, ensuring solutions meet performance, scalability, security, cost, and reliability requirements.
• AI Observability: Define and implement an AI observability framework covering model performance monitoring, data drift detection, prediction quality tracking, and system health across all production AI systems. Establish real-time and batch monitoring pipelines for model inference using tools such as Evidently AI, Arize, WhyLogs, Fiddler, or equivalent open-source platforms. Design standardized dashboards and alerting for model degradation, data skew, latency SLO breaches, and feature store anomalies. Build feedback loop infrastructure to capture ground-truth labels and enable continuous model evaluation in production. Define observability standards for GenAI and LLM systems, including hallucination rate tracking, prompt/response logging, latency percentiles, and cost-per-query attribution. Partner with MLOps and Platform Engineering to embed observability as a first-class requirement in every AI system from Day 1.
• AI Security: Serve as the AI security authority for Company, owning the threat model for all AI and ML systems in production. Define and enforce secure-by-design standards for model development, training data handling, inference APIs, and GenAI integrations. Architect defenses against AI-specific attack vectors, including prompt injection, model inversion, adversarial inputs, data poisoning, and supply chain risks in open-source model adoption. Establish data privacy controls for AI pipelines, ensuring compliance with applicable regulations (e.g., CCPA) and internal data governance policies. Lead AI red‑teaming and adversarial testing exercises to proactively identify and remediate security gaps before production deployment. Partner with Information Security, Legal, and Enterprise Risk to maintain an AI risk register and align AI security posture with the organization’s broader cybersecurity framework. Define guardrails, content filtering, and human-in-the-loop safeguards for all customer-facing and associate-facing GenAI applications.
• MLOps, GenAI & Governance: Establish MLOps and AIOps practices, including CI/CD for models, automated retraining, monitoring, drift detection, and cost controls. Define standards for Generative AI and LLM usage, including multi-RAG architectures, MCP, and vector search. Define prompt orchestration, tool‑calling, and agentic workflow patterns. Ensure AI solutions comply with data privacy, security, and responsible AI principles. Partner with Security, Legal, and Enterprise Architecture to align AI solutions with governance and risk standards.
• AI Productivity Tooling: Mandate personally mandate and model the daily use of AI-native productivity tools across all architecture and delivery work. Evaluate, recommend, and govern the enterprise use of tools including: Microsoft Copilot – for productivity, code assistance, and enterprise knowledge retrieval. Cursor – for AI‑assisted development and code generation within engineering workflows. Glean – for enterprise search, institutional knowledge management, and AI‑powered information retrieval. Claude (Anthropic) – for complex reasoning, document synthesis, and agentic task automation. Equivalent or emerging AI productivity platforms as the market evolves. Define standards and guardrails for enterprise AI tool adoption, including data classification policies governing what information may be shared with each platform. Train and upskill engineering and cross‑functional teams on effective use of AI productivity tooling to multiply output and reduce time‑to‑delivery.
• Technology Evaluation, Implementation & Delivery: Work closely with AI Engineers, ML Engineers, Data Engineers, and platform teams to ensure architectures are production‑ready and executable. Provide hands‑on guidance during implementation, including reference code, pipelines, schemas, and infrastructure patterns. Evaluate and recommend AI SaaS solutions, cloud services, and frameworks (AWS, Azure, GCP, Databricks, Snowflake, etc.). Lead build vs. buy vs. open-source decisions and support vendor selection for AI capabilities.

Required Qualifications

• 9+ years of experience in software, data, or AI engineering, with 5+ years in AI/ML architecture roles.
• Proven experience designing and delivering production AI solutions specifically in retail, e-commerce, supply chain, or consumer-facing industries — this is a non‑negotiable requirement.
• Deep hands‑on expertise with open-source AI/ML ecosystem: Hugging Face Transformers, LangChain, LlamaIndex, MLflow, Ray, Feast, Evidently, or equivalent.
• Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow, scikit-learn).
• Experience with modern data architectures: lakehouse, streaming, batch pipelines; platforms such as Databricks and Snowflake.
• Demonstrated experience designing AI observability systems — including model monitoring, drift detection, and production feedback loops.
• Working knowledge of AI security threat models, including prompt injection, adversarial attacks, and secure LLM deployment practices.
• Hands‑on experience with cloud platforms and managed AI/ML services (AWS SageMaker, Azure ML, Vertex AI, or equivalent).
• Established practice of using AI productivity tools (e.g., Copilot, Cursor, Claude, Glean, or similar) in daily engineering and architecture work.
• Excellent communication skills with the ability to explain complex architectures to both technical and business stakeholders.

Preferred Qualifications

• Experience building or scaling enterprise AI platforms or AI Centers of Excellence.
• Contributions to open-source AI projects or published architecture patterns.
• Experience with AI red‑teaming, adversarial testing, or formal AI risk assessment frameworks.
• Familiarity with retail‑specific platforms: Manhattan WMS, Blue Yonder, Aptos POS, Salesforce Commerce Cloud, or equivalent.
• Cloud or AI certifications (AWS ML Specialty, Azure AI Engineer, GCP Professional ML Engineer).

Explore our benefits site to discover all the perks and support we offer! From health coverage to financial and personal wellness, we've got you covered—check it out today! benefits.fivebelow.com/public/welcome Five Below is an Equal Opportunity Employer.

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, age, national origin, disability, protected veteran status, gender identity or any other factor protected by applicable federal, state, or local laws.

Five Below is committed to working with and providing reasonable accommodations for individuals with disabilities.

If you need a reasonable accommodation because of a disability for any part of the employment process, please submit a request and let us know the nature of your request and your contact information.

Five Below is a leading growth retailer offering trend‑right, extreme value, high‑quality products loved by the kid and the kid in all of us. We believe life is better when customers are free to 'let go & have fun' in an amazing experience filled with unlimited possibilities. With most items priced between $1 and $5 and some extreme‑value items priced beyond $5, Five Below makes it easy to say YES! to the newest, coolest stuff across awesome Five Below worlds: Candy, Style, Party, Room, Create, Tech, Sports, and New & Now. Founded in 2002 and headquartered in Philadelphia, Pennsylvania, Five Below today has over 1,900 stores in 46 states.