Note: The job is a remote job and is open to candidates in USA. Vista Equity Partners is a global investment firm focused on enterprise software, data, and technology-enabled organizations, with a Value Creation Team that partners with portfolio companies to accelerate growth and operational performance. The Associate Director, AI Ops Engineering will design, build, and operate production-grade agentic AI platforms and applications, spanning agent architecture, interfaces, data, infrastructure, governance, and observability. The role also supports platform onboarding, establishes technical standards, evaluates emerging AI technologies, and collaborates with product, engineering, and cross-functional stakeholders.
Responsibilities
- Design, build, and iterate on agentic AI systems, moving from validated concept to production grade capability with clear stage gates and measurable outcomes
- Design and build intuitive, accessible interfaces for agentic AI products, partnering with solution owners to translate concepts and prototypes into production-ready experiences
- Own hands-on implementation of agent architectures (single-agent, multi-agent, human-in-the-loop) across a range of enterprise use cases, and build the production stack that supports them, including interfaces, APIs and data integrations, identity and access, data and memory, infrastructure, and observability
- Develop and stress-test reference implementations for core agentic capabilities, including tool use, memory, planning, orchestration, and inter-agent communication, to establish what works reliably at enterprise scale
- Design abstraction layers and reusable infrastructure components that preserve vendor independence across large language model (LLM) providers, orchestration frameworks, and cloud environments
- Help onboard and enable AI tools built across the practices onto a shared platform, so that capabilities run on common infrastructure, standards, and governance
- Define and evolve technical standards for agent development: model selection, prompt architecture, autonomy calibration, observability, and guardrails, ensuring every capability is built on a foundation that can survive production
- Establish evaluation frameworks and scoring rubrics for agent performance, reliability, and safety that can be operationalized consistently across the platform
- Partner across product, engineering, and cross-functional stakeholders, translating validated field patterns into reusable platform capabilities and managing stakeholders across multiple teams and companies simultaneously
- Continuously assess the frontier of agentic AI, including new models, frameworks, tooling, and architectural patterns, and translate findings into concrete recommendations for what to build, buy, or watch
- Serve as a practitioner voice on generative AI and agentic systems, contributing to Vista's thought leadership and helping shape the platform's technical direction in partnership with leadership
Skills
- Generative AI, including large language models (LLMs), inference, retrieval-augmented generation (RAG) architectures, and diffusion models
- Agentic architectures, autonomous agents, and multi-agent systems
- Front-end development and user interface and user experience (UI/UX) design patterns for complex, data-rich, and AI-native applications
- Familiarity with modern design and prototyping tools and AI-assisted design workflows
- Cloud AI platforms across Amazon Web Services (AWS), Microsoft Azure, and Google Cloud (GCP)
- AI model development, deployment, and lifecycle management
- Prompt engineering and model fine-tuning
- Machine learning and deep learning fundamentals
- Platform abstraction and vendor-independent architecture design
- Shipping AI applications to production environments, and operating them for reliability, observability, and cost
- Rapid proof-of-value delivery and compressed development timelines
- Cross-organizational collaboration and stakeholder management across multiple companies simultaneously
- AI maturity assessment and improvement planning
- Translating complex technical concepts for executive audiences
- Problem-solving and analytical thinking in ambiguous environments
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related field
- 3+ years of experience in AI/ML platform architecture and development, with deep recent experience (2+ years) in generative AI and agentic architectures in production applications
- Demonstrated track record of shipping AI applications to production environments, not just prototypes
- Strong understanding of public cloud AI services and the ability to architect vendor-agnostic solutions with appropriate abstraction layers
- Excellent communication, presentation, and interpersonal skills
- Depth in front-end engineering and UI/UX design, including hands-on experience shipping polished, user-facing interfaces, is a strong plus for this role
- Experience within private equity portfolio companies, consulting, or multi-client environments is a strong plus
Benefits
- An annual cash bonus
- A comprehensive benefits package
Company Overview
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