Manager LLM Architecture

Job Description

ABOUT THE TEAM The Generative AI Platform team owns the company-wide stack for Large Language Model integration, including retrieval-augmented generation (RAG), prompt orchestration, vector-database indexing, and evaluation tooling. We partner with product, design, and domain experts to convert research breakthroughs into secure, scalable, and delightful customer experiences. As our Lead LLM Architect you will set the technical vision, design the architecture, and guide engineers building reusable AI services across web, mobile, and backend products. At ABC, we love entrepreneurs because we are entrepreneurs. We know how much grit it takes to start your own business and grow it into something that lasts. We roll our sleeves up, we act fast, and we learn together. You will be working closely with talented software engineers and senior engineering leaders to optimize and build upon our single integration platform strategy. WHAT YOULL DO: Partner with engineering, product, and design leaders to define a clear Gen-AI vision, strategy, and roadmap for ABCs platform. Empower your team to deliver AI-powered solutions in a simple, reliable, and sustainable way. Develop and support engineers in their personal growth and career progression; act as a mentor and coach. Contribute to engineering-wide initiatives that make ABC an exceptional place to work for ambitious, highly motivated engineers. Gain deep product understanding of our fitness-tech domain and share that knowledge across the team. Teach, mentor, and coach other engineers on Gen-AI best practices, secure coding, and architectural excellence. Facilitate daily stand-ups and planning; remove blockers, ensure goals are met, and embed lessons learned from retrospectives and experiments. Provide hands-on leadership across our technical stack (Java, .NET, Golang, React/React Native) while introducing LLM components (OpenAI/Azure OpenAI, LangChain, vector DBs). Leverage cloud expertise (AWS or Azure) to deploy scalable, cost-efficient AI micro-services on Kubernetes with IaC (Terraform/Bicep). Architect and oversee API-orchestration layers that expose LLM capabilities as secure, versioned services consumed by web and mobile products. Embed Responsible-AI guardrailsbias checks, audit logging, safety filtersand champion enterprise-grade security, privacy, and compliance. Oversee best-practice adoption for software engineering, DevSecOps, and quality; ensure industry standards and legal requirements are built into every release. Communicate clearly with stakeholders and senior management—articulating platform strategy, trade-offs, and technical risks in plain English. WHAT YOU’LL NEED: Bachelor’s degree in Computer Science (or related field) preferred; Master’s or PhD in AI / ML is a plus. 8–10 + years of hands-on software-engineering experience, including 3 + years in technical-lead or people-management roles driving architecture decisions. Deep expertise with Gen-AI stacks: OpenAI / Azure OpenAI, LangChain / LlamaIndex, embedding workflows, and vector databases (Pinecone, Weaviate, Milvus, pgvector). Cloud mastery on AWS and/or Azure—including Kubernetes, GPU/TPU provisioning, Infrastructure-as-Code (Terraform/Bicep), and cost-governance. Strong coding skills in Node.js and/or Python, plus ability to dive into Java, .NET, React / React Native when needed (“roll-up-your-sleeves” mindset). Proven track record designing and operating large-scale, low-latency AI micro-services used by thousands of customers or millions of requests. Solid grounding in software-architecture patterns, system design, and DevSecOps; able to embed Responsible-AI guardrails (bias checks, safety filters, audit logging). Exceptional written and verbal communication, comfortable translating complex AI concepts for both technical and non-technical stakeholders. Demonstrated leadership and mentoring skills—cultivating curiosity, psychological safety, and an innovation mindset within diverse teams. Strategic-planning & project-management prowess: OKRs, Agile/Scrum, roadmap prioritisation, and cross-functional delivery in fast-moving environments. “Experience partnering with OpenAI or Azure OpenAI product teams, or contributing to OSS Gen-AI frameworks, is a strong plus.”