Principal AI Architect
Tricentis · Austin, TX · 3 wk ago
Art & CreativeFull-time
Key Responsibilities
- Architect, design, and evolve a scalable, secure AI platform and reference architecture that enables rapid development of AI-powered product capabilities
- Drive strategic decision-making across: Model selection and fine-tuning, Retrieval-Augmented Generation (RAG) Agent frameworks, Data pipelines, Inference optimization
- Evaluate and integrate: Open-source and commercial LLMs, Vector databases, Feature stores, MLOps platforms
- Collaborate cross-functionally with Product, Engineering, Architecture, and UX to define AI requirements and priorities
- Lead and influence engineering teams (directly and indirectly), fostering a culture of innovation and architectural excellence
- Lead architecture reviews, technical governance, and long-term platform planning
- Agentic AI & Advanced Systems
- Provide architectural direction for Agentic AI systems, including: Workflow orchestration, Multi-agent collaboration, Context management, Safety controls, Autonomous decision-making frameworks
- Design and implement LLMOps and AIOps practices for production systems
- Drive observability practices for monitoring agent behavior and system performance
- Define guardrails for: Agent interactions, Memory usage, Context boundaries, Governance & Standards
- Define and enforce: Target-state architectures, Principles and standards for AI/ML, Responsible AI and ethical frameworks (e.g., GDPR, NIST AI RMF)
- Define processes for metadata extraction and management, enabling granular access control
- Develop and maintain AI reference architectures and best practices
Qualifications
- Experience 8+ years of experience as a Senior, Lead, or Principal Engineer/Architect
- Hands-on experience with AI and ML systems in production environments
- Proven ability to lead large-scale architectural initiatives and influence cross-functional decisions
- Strong programming proficiency in: Python (expert-level required), Java, TypeScript, Node.js, or similar
- Experience with AI frameworks such as: LangGraph, LangChain, LlamaIndex, Semantic Kernel, AutoGen AI / ML
- Deep experience with: Large Language Models (LLMs), Embeddings, Vector databases, RAG architectures, Model serving frameworks
- Hands-on experience with Agentic AI patterns, including: Autonomous agents, Tool usage, Multi-agent coordination, Goal-directed planning
- Strong background in cloud platforms: AWS, Azure, or GCP
- Experience with: Containerization, Serverless technologies, Distributed systems, Security & Systems Design
- Experience designing secure AI systems, including: Data privacy, Encryption, Compliance, Responsible AI practices
- Solid understanding of: API integration patterns, Messaging systems, Event-driven architectures, Modern Architecture
- Excellent communication, problem-solving, and technical leadership skills
- Proven experience building scalable, high-performance distributed systems