Overview As Senior Technical Architect, you will define and govern enterprise Generative AI architectures to enable AI-enabled business processes and knowledge solutions. You'll connect AI capabilities with enterprise data, APIs, and applications while providing technical leadership from concept to production. You'll collaborate with engineering, data, cloud, security, and business teams to drive secure, scalable, and reusable patterns. This role offers impact across RAG, agents, enterprise search, and knowledge retrieval in a large enterprise. You will shape standards, reference architectures, and governance for responsible AI delivery.
Compensation / Benefits- Comprehensive medical, dental, vision coverage
- Generous paid time off including holidays
- Life insurance and disability coverage
- 401K with company matching
- Educational reimbursement
- Employee discounts
Responsibilities- Define and evolve the enterprise reference architecture for Generative AI applications and AI agents
- Design architectures for RAG, conversational AI, enterprise search, agentic workflows, and AI-enabled applications
- Establish reusable patterns for model access, model gateways, prompt/context management, embeddings, vector/semantic search, knowledge retrieval, and agent orchestration
- Design secure integration patterns connecting AI agents with enterprise applications, APIs, data, tools, events, and workflow services
- Define identity, authorization, human-in-the-loop, and approval patterns for AI agents and higher-risk actions
- Establish standards for AI security, evaluation, observability, tracing, auditability, resiliency, performance, and cost management
- Evaluate AI models, platforms, frameworks, and emerging technologies and recommend appropriate enterprise standards
- Develop reference architectures, reusable components, technical standards, architecture diagrams, and reference implementations
- Conduct architecture and technical design reviews and provide technical leadership to development teams
- Partner with Security, Privacy, Data Governance, and Responsible AI teams to embed appropriate controls into AI solutions
- Ensure architectures are scalable, maintainable, API-driven, loosely coupled, and model/provider agnostic where appropriate
Key requirements- Bachelor's degree in Computer Science, Engineering, Information Systems, or related field, or equivalent experience
- 10+ years of software, solution, cloud, or enterprise architecture experience including cloud-native apps
- Strong understanding of Generative AI, LLMs, RAG, embeddings, semantic/vector search, and enterprise knowledge retrieval
- Experience designing AI agent architectures including tool calling, context management, orchestration, memory, and human approval
- Strong experience with APIs, microservices, event-driven architecture, integration patterns, and IAM
- Experience with Python and modern application-development technologies, and guiding engineering teams
- Strong understanding of structured and unstructured data architectures
- Experience with cloud security including IAM, secrets management, encryption, logging, monitoring, and secure API integration
- Ability to translate complex business requirements into secure, scalable architectures
- Strong technical communication, architecture documentation, and stakeholder-management skills
- Strong communication and collaboration
- Strategic thinking and governance mindset
- stakeholder-management
- Generative AI / LLM-based architectures
- RAG, semantic/vector search, knowledge retrieval
- AI agent frameworks and orchestration
