Partner with the SVP of Technology to define technical strategy, architecture standards, platform direction, and modernization priorities.
Review major architecture decisions across software, data, AI/ML, cloud, infrastructure, and integration platforms.
Challenge weak technical designs and guide teams toward scalable, maintainable, and cost-effective solutions.
Serve as the SVP's delegate in technical reviews, planning discussions, vendor evaluations, and cross-functional initiatives.
AI, Data & Platform Leadership
Lead and guide AI, ML, data engineering, analytics, and automation initiatives.
Help teams move AI ideas from prototype to production-grade systems.
Provide direction on RAG, agentic systems, LLMOps, reasoning models, model evaluation, data pipelines, data governance, observability, and responsible AI practices.
Ensure AI and data platforms are reliable, measurable, secure, and aligned to business outcomes.
Engineering Execution
Work with technology leads to improve delivery discipline, technical quality, and engineering consistency across teams.
Identify execution risks, technical debt, infrastructure bottlenecks, and unclear ownership.
Help unblock complex technical and organizational issues.
Drive measurable improvements in reliability, delivery speed, system performance, and engineering productivity.
People & Technical Leadership
Coach tech leads, architects, staff engineers, engineering managers, data engineers, ML engineers, and software engineers.
Raise the technical bar through architecture reviews, mentoring, design critiques, and hands-on guidance.
Support hiring, onboarding, technical career growth, and succession planning.
Identify and develop future technical leaders.
Infrastructure, Cost & Operational Efficiency
Partner with cloud, DevOps, infrastructure, and finance teams to manage technology cost and platform efficiency.
Review cloud spend, tooling, licensing, vendor usage, and build-versus-buy decisions.
Drive cost optimization without compromising scalability, security, reliability, or product quality.
Establish KPIs around system reliability, infrastructure efficiency, AI quality, platform reuse, and engineering effectiveness.
Other duties as assigned.
Required Qualifications
Bachelor's degree in software engineering or a related technical field.
10+ years of experience in software engineering, architecture, data engineering, AI/ML, cloud infrastructure, or platform engineering.
5+ years leading technical teams, architects, engineering managers, or senior engineers, preferably in a global environment.
Strong technical depth across modern software architecture, APIs, distributed systems, cloud platforms, DevOps, and data platforms.
Hands-on understanding of AI/ML systems, including LLMs, reasoning models, multimodal models, embeddings, rerankers, RAG, agent workflows, model evaluation, and production deployment.
Experience evaluating when to use general-purpose LLMs, smaller task-specific models, reasoning models, and traditional ML models based on accuracy, latency, cost, risk, and business value.
Familiarity with prompt engineering, structured outputs, tool/function calling, agentic workflows, model orchestration, hallucination reduction, and LLM observability.
Ability to guide teams on LLM selection, inference cost optimization, model safety, guardrails, data privacy, and production deployment.
Understanding of emerging AI architecture patterns, including multi-agent systems, reasoning loops, retrieval-augmented generation, memory, model routing, and human-in-the-loop review.
Experience with data engineering, analytics platforms, lakehouse/warehouse architecture, data quality, and governance.
Strong judgment in technical decision-making, cost tradeoffs, risk management, and execution planning.
Ability to influence senior technical leaders without needing direct authority over every team.
Strong communication skills with executives, product leaders, engineers, and business stakeholders
Abi
Additional Information
Job Description
he Senior Director, Technology Strategy & AI Engineering, will report to the SVP of Platform and serve as his key technical and operational partner. This role will act as the SVP's second-in-command across software engineering, data engineering, AI/ML, infrastructure, architecture, cost optimization, and technical execution.
This person will work through engineering managers, architects, and technology leads to driving technical direction, improve execution quality, solving complex problems, and ensuring teams are building scalable, secure, cost-efficient, and future-ready platforms. This person will be part of a fast-paced, outcome-focused organization and will be hands on.
The ideal candidate is a hands-on technologist and strong people leader who can operate at both strategic and execution levels. This position is hybrid in our Atlanta, GA office.
Communitybrands · Atlanta, GA