The University of Texas at Austin · 2 months ago
Director of AI Platforms, Texas Institute for Electronics
AUSTIN, TX
Full-time
Onsite
Director/Executive
8+ years expThe University of Texas at Austin is a leading educational institution, and they are seeking a Director of AI Platforms for the Texas Institute for Electronics. This role involves driving the design, deployment, and optimization of enterprise-grade AI solutions, leading technical innovation, and managing a high-caliber engineering team to deliver impactful AI capabilities.
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Responsibilities
Define and lead the software architecture and implementation roadmap for a scalable, modular AI infrastructure platform. You will work across backend, orchestration, and deployment layers—focusing on performance, security, and reliability
Build and manage a high-caliber engineering team, including backend developers, platform engineers, and site reliability engineers. You will be responsible for mentoring, hiring, and setting a culture of technical excellence and operational discipline
Own core services that power AI pipelines, including APIs for data ingestion and transformation, orchestration of model inference jobs, and integration with LLM orchestration layers and vector stores
Establish technical strategy and design standards that support rapid prototyping, automated testing, and code reuse across teams. You will define best practices and lead by example in system design, code reviews, and architectural discussions
Lead on-premise deployment strategy, ensuring our stack is optimized for hybrid environments. You will manage challenges around air-gapped deployments, resource management, and update rollouts in constrained environments
Collaborate cross-functionally with AI engineering, product management, and customer success to align engineering priorities with product goals. You’ll help translate high-level needs into deliverable milestones
Implement and maintain CI/CD pipelines and DevOps best practices, focusing on security, observability, rollback safety, and developer productivity
Develop and enforce SLAs/SLOs for critical services, putting in place monitoring, alerting, and incident response practices that ensure uptime and stability in enterprise-grade deployments
Stay on top of evolving technologies in distributed systems, containerization, service mesh, observability, and developer tooling—bringing in the best ideas to future-proof our platform
Other related functions as assigned
Qualification
Required
BS in Computer Science, Engineering, or a related field
8 or more years of software engineering experience, including 3 or more years focused on AI/ML and LLM-based applications
Deep knowledge of LLM architectures and tools – you understand transformer models inside and out and are fluent in the surrounding ecosystem (from tokenization and embedding techniques to prompt engineering and fine-tuning methods)
Proven track record of productionizing LLM applications end-to-end. You have built and deployed AI-powered solutions (using both commercial APIs and open-source models) into real-world production environments – including experience with on-prem or private cloud deployments of AI systems
Hands-on experience with the LLM tech stack: this includes building pipelines with vector databases (for embedding storage/search) and using LLM orchestration frameworks like LangChain or LlamaIndex to compose prompts, tools, and data retrieval
Experience with modern model serving and scaling – familiarity with frameworks such as vLLM, LMDeploy, Ray (for distributed inference), or Triton Inference Server to optimize runtime performance of large models
Exceptional engineering and problem-solving skills. You can design elegant solutions for complex challenges and debug issues across the ML stack (data, model, infrastructure) when things go wrong
Excellent communication skills. You know how to articulate complex technical concepts clearly and adjust your message for engineers, founders, or other stakeholders. You can document architectures, write clear project plans, and mentor others by explaining the 'why' behind technical decisions
You have the ability to work effectively in fast-paced environments. You have the ability to act with urgency, adapt quickly to new information, and take ownership of
Execution mindset. You have demonstrated experience driving projects forward in a hands-on role without heavy process or management overhead. You excel at managing multiple priorities, staying organized, and delivering results in a lean team setting
Preferred
MS or PhD in Computer Science, Machine Learning, or a related discipline
Prior technical leadership experience. Experience leading an engineering team or serving as a tech lead for complex AI/ML projects. Ability to mentor others and experience managing project roadmaps or teams in previous roles
Domain expertise in NLP/LLMs. Publications, open-source contributions, or recognized expertise in the NLP/LLM field (e.g. contributions to Transformer libraries, research in language modeling, etc.) will set you apart
Enterprise AI experience. Familiarity with the unique challenges of applying AI in enterprise settings – such as handling sensitive data, ensuring compliance (e.g. GDPR, SOC2), or integrating with enterprise IT systems – is a plus
Benefits
Competitive health benefits (employee premiums covered at 100%, family premiums at 50%)
Voluntary Vision, Dental, Life, and Disability insurance options
Generous paid vacation, sick time, and holidays
Teachers Retirement System of Texas, a defined benefit retirement plan, with 8.25% employer matching funds
Additional Voluntary Retirement Programs: Tax Sheltered Annuity 403(b) and a Deferred Compensation program 457(b)
Flexible spending account options for medical and childcare expenses
Robust free training access through LinkedIn Learning plus professional conference opportunities
Tuition assistance
Expansive employee discount program including athletic tickets
Free access to UT Austin's libraries and museums with staff ID card
Free rides on all UT Shuttle and Austin CapMetro buses with staff ID card
Company
The University of Texas at Austin
The University of Texas at Austin is one of the largest public universities in the United States.
10001+ employees
H1B Sponsorship
The University of Texas at Austin has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (282)
2024 (210)
2023 (175)
2022 (186)
2021 (187)
2020 (190)
Funding
Current Stage
Late StageTotal Funding
unknownKey Investors
Republic Capital Group
2022-09-14Series Unknown
Leadership Team
Will Whiting
Chief Development Officer
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