Principal AI Technical Architect (AI Platforms)

Quick Facts

• Role: Principal-level AI technical architecture bridging system design and hands-on AI engineering

• Focus: Agentic intelligent systems, LLM integration, RAG, and productionization (LLMOps)

• Collaboration: Cross-functional with AI, data, product, and engineering; partner with senior client stakeholders

Description

Design, guide, and evolve next-generation agentic intelligent AI system architectures. Bridge high-level system design with hands-on AI engineering to enable scalable architectures for AI-driven applications, including seamless integration of large language models (LLMs), data pipelines, and enterprise systems. Own solution blueprints for RAG and agent orchestration, and support delivery from prototype to production with observability, governance, and responsible AI practices.

Responsibilities

• Define scalable, low-latency, modular AI and LLM solution architectures

• Design agentic AI workflow automation using memory, agentic reflection, and task planning

• Create AI integration patterns such as RAG for model orchestration, context management, prompt orchestration, and external system connectivity

• Establish architectural blueprints, design principles, and governance frameworks for model versioning, data lineage, and responsible AI

• Prototype and validate model architectures, RAG flows, and agent orchestration via proof-of-concepts

• Evaluate and integrate emerging AI frameworks and tools (e.g., LangChain, LlamaIndex, LangGraph, Semantic Kernel)

• Develop solutions using agent orchestration engines (e.g., n8n, Retool, OpenAI Agentkit, Microsoft Copilot Studio, AWS Flows)

• Manage production readiness: performance, observability, and governance from prototype to production

• Define LLMOps standards for versioning, testing, and monitoring of models and AI services

• Lead communication with technical and non-technical audiences; deliver workshops, presentations, and consensus-building

• Mentor and QA junior team members; oversee delivery quality for modules

• Stay current on distributed AI systems, RAG, retrieval/indexing strategies, and agent frameworks; contribute to proposals and thought leadership

Requirements

• Bachelor’s degree in IT/business administration/computer science/information systems or related field (Master’s preferred)

• 10+ years of technology consulting or software engineering; 5+ years in architecture discipline

• Strong software architecture and distributed systems design foundation

• Proven experience designing/scaling AI/ML or LLM-based applications

• Proficiency in one or more languages: Python, JavaScript, TypeScript, Node.js, TensorFlow/Keras, or PyTorch

• Familiarity with modern AI/agent frameworks (e.g., LangChain, LangGraph, Google ADK, Semantic Kernel, AutoGen, CrewAI, LlamaIndex)

• Understanding of agentic AI capabilities/tools including memory, RAG, vector databases, function-calling, observability, safety, deployment strategies, and governance

• Knowledge of cloud architecture, data management, and API-based system integration

• Experience deploying autonomous/semi-autonomous agents across multi-cloud/hybrid environments

• Ability to explain complex topics to senior executives

• Willingness to travel to client sites (often significant)

Benefits

• Opportunity to work across disciplines with a unified strategic + hands-on approach

• Supportive environment working with expert problem-solvers delivering digital solutions

• U.S. compensation: $230,000 base salary, discretionary annual performance bonus, and retirement contribution eligibility

• Medical, dental, and vision with $0 premiums for employees (and eligible family members)

• Gym membership and fitness reimbursement; generous paid time off

• Paid parental leave and additional family benefits

• Fully vested retirement contributions annually