Senior AI Engineering

Purpose: The Senior AI Engineer will design, build, and operate the framework and platform capabilities that enable agentic solutions across Floor & Decor — and will build flagship agentic products on that platform to prove it out. The role covers the full delivery lifecycle: planning, designing, configuring, testing, implementing, documenting, and maintaining AI solutions on Microsoft Azure, integrated with the company's operational systems. The mandate is durable capability, not a single product. Individual agentic solutions will come and go — some will graduate to other teams, some will be retired — but the substrate they're built on is what this team owns: the tool and integration layer, context and memory management, evaluation and observability, guardrails, and the paved road that lets the next workflow ship in weeks rather than quarters. This is a hands-on senior IC role, not a research or data science position. We want an engineer with first-principles command of backend systems who has moved into AI engineering — someone who treats LLMs and agents as components in a well-architected distributed system, held to the same standards of reliability, observability, security, and cost control as any other production dependency. Technical leadership is exercised through architecture, code quality, and influence rather than direct reports. Hybrid: in-office Monday, Tuesday, and Thursday. Minimum Eligibility Requirements Engineering Foundation 7–10 years of software engineering experience with increasing scope and ownership. Deep proficiency in at least one of C#/.NET, Java, Node.js/TypeScript, or Python — first-principles backend understanding matters more than the specific language. Python is a plus, not a requirement. Service-based/microservice architectures, RESTful API design, and async communication — versioning, contracts, error semantics, backward compatibility. Cloud-based serverless microservices in production (Azure Functions, Container Apps, or equivalent). Event-driven architecture: queues, pub/sub, idempotency, retries, dead-letter handling. Solid data fundamentals: relational/NoSQL modeling, query performance, transactional correctness. Ownership of code quality — testing, review, CI/CD as normal practice. AI Engineering Designed and deployed agentic solutions shipped and operated in production, not prototypes or POCs. RAG is one tool in the kit, not the definition of the job. Harness engineering: context construction, tool/function-call interfaces, multi-step planning, memory and state, structured output, guardrails, human-in-the-loop checkpoints, graceful failure. Azure OpenAI, Azure AI Search (vector/index), related Azure infrastructure. Azure AI Foundry or AWS Bedrock also applies. Agent/LLM orchestration frameworks (LangChain, LangGraph, or similar) and MCP or comparable tool-calling patterns. Fluency with AI failure modes — hallucination, prompt injection, data leakage, runaway tool loops — and mitigations. Sound judgment on when an agent is (and isn't) the right tool, and how to bound and validate its output. AI-Augmented Development Daily fluency with agentic coding tools (Claude Code, Cursor, Copilot, Devin, or equivalent); Claude Code is our standard. A specific point of view on where these tools help and don't, and how to review model-generated code, backed by measurable impact on throughput and quality. Cloud, Security, and Delivery Azure fundamentals: compute, storage, networking, IAM; secrets management and network boundaries. Agile/scrum methodologies — sprint ceremonies, estimation, backlog grooming. Working knowledge of Angular or a comparable front-end framework. Clear communication with technical and non-technical partners; comfortable moving from an ambiguous problem to a scoped, shippable increment. Education Bachelor's degree in Computer Science, Engineering, or related field, or equivalent experience. Demonstrated capability outweighs credentials. Essential Job Functions Agentic Platform & Framework Engineering Design, build, and evolve the shared framework — scaffolding, tool/integration interfaces, context and memory management, evaluation, guardrails, observability — that lets teams build and operate agentic solutions. Turn one-off implementations into reusable building blocks: templates, harness components, MCP server patterns, evaluation harnesses, deployment pipelines. Maintain MCP integrations with enterprise systems (inventory, merchandising, and beyond) so agents ground in live operational data. Define standards and reference architectures; document decisions for reliability, scalability, security, and observability in Azure. Agentic Solution Delivery Design, build, and operate production agentic solutions end to end to deliver business value and harden the platform. Apply the right technique: tool calling, multi-step planning, retrieval, memory, human-in-the-loop review, or a deterministic service where an agent is wrong. Tune retrieval where warranted — chunking, vector indexing, ranking, context engineering on Azure AI Search. Contribute across the stack, including Angular and the Python LLMOps layer. Support transition of mature products to partner teams via docs, runbooks, and knowledge transfer. Evaluation, Observability & Operations Establish evaluation/regression testing as first-class: eval sets, LLM-as-judge scoring, task-level metrics, CI regression gates. Own retrieval evaluation with Ragas (faithfulness, relevance, context precision). Instrument systems with Langfuse and Azure Monitor — tracing, latency, cost attribution, tool-call success, failure modes — and act on the telemetry. Manage AI cost/performance: token budgeting, caching, model routing, latency. Own production services, including on-call, incident response, and troubleshooting of agent behavior, retrieval quality, hallucination, and integration issues. Engineering Practice & Collaboration Apply spec-driven development. Set the standard for AI-augmented development, including review discipline. Conduct code reviews and mentor peers through technical influence. Partner with stakeholders to scope requirements and prioritize the backlog. Consult for teams adopting the platform. Participate in agile ceremonies as a senior voice, communicate trade-offs clearly, and partner with security/data teams on governance, PII handling, prompt injection defense, and responsible use. Innovation & Quality Evaluate emerging agent tooling and Azure OpenAI/AI Foundry updates; prototype improvements. Maintain CI/CD, IaC, and security practices for AI workloads, and keep reducing the cost and time to bring the next agentic solution to production. Nice to Have Spec-driven development; internal developer platforms/SDKs; building/publishing MCP servers; evaluation frameworks (Ragas, G-Eval, LLM-as-judge); observability tooling (Langfuse or equivalent); retrieval beyond Azure AI Search (pgvector, Pinecone, Elastic, hybrid search); multi-agent orchestration or durable workflow engines; IaC (Bicep, Terraform, ARM); fine-tuning (LoRA/PEFT); LLMOps tooling (MLflow, W&B, Azure ML); retail systems (POS, OMS, merchandising); Center of Excellence experience; open source, writing, or speaking in AI engineering. Our Technology Stack Layer - Technologies Front End - Angular, TypeScript Back End / LLMOps - Python, C#/.NET, Node.js/TypeScript, REST APIs, serverless microservices (Azure Functions, Container Apps) AI / LLM - Azure OpenAI, Azure AI Foundry, Azure AI Search, agentic architectures, RAG where warranted Orchestration & Integration - LangChain / LangGraph, MCP Evaluation - Ragas, eval sets, LLM-as-judge, CI regression gates Observability - Langfuse, Azure Monitor, Application Insights Cloud & DevOps - Microsoft Azure, CI/CD pipelines, IaC (Bicep/Terraform), Agile/Scrum AI-Augmented Development - Claude Code Integrations - Enterprise systems — inventory, merchandising, and beyond — via MCP Why Join Our AI Center of Excellence Build the foundation, not just the feature — the framework every agentic workflow at Floor & Decor is built on. Ship production agentic products used by thousands of associates across a national retail footprint and see the impact in real stores. This is greenfield scope in a mature company: the platform is being defined now, with real budget, real users, and real systems to integrate with. Competitive pay and benefits, plus room to grow into broader AI architecture and leadership as the Center of Excellence scales. Benefits & Rewards Bonus opportunities at every level Non-traditional retail hours (we close at 7p!) Career advancement opportunities Relocation opportunities across the country 401k with discretionary company match Employee Stock Purchase Plan Referral Bonus Program 80 hrs. annualized paid vacation (full-time associates) 4 paid holidays per year (full-time hourly store associates only) 1 paid personal holiday of associate’s choice and Volunteer Time Off program Medical, Dental, Vision, Life and other Insurance Plans (subject to eligibility criteria) Equal Employment Opportunity Floor & Decor provides equal employment opportunities to all associates and applicants without regard to age, race, color, religion or creed, national origin or ancestry, sex (including pregnancy), sexual orientation, gender, gender identity, disability, veteran status, genetic information, ethnicity, citizenship, or any other category protected by law. This policy applies to all areas of employment, including recruitment, testing, screening, hiring, selection for training, upgrading, transfer, demotion, layoff, discipline, termination, compensation, benefits and all other privileges, terms and conditions of employment. This policy and the law prohibit employment discrimination against any associate or applicant on the basis of any legally protected status outlined above. Show more Show less