Senior AI Architect
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GenesysAI, Cloud Computing
United StatesFull-TimeSenior
Salary$134,900.00 - $237,300.00 / year
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Job Details
- Required Skills
- Artificial IntelligenceCloud ComputingMachine LearningRESTful APIsNLP
Requirements
- Extensive hands-on experience architecting modern AI solutions using traditional machine learning, NLU and NLP, retrieval-based systems, LLMs, orchestration patterns, tool use, and agentic AI approaches.
- Demonstrated architectural judgment and ability to make and defend tradeoffs across model selection, latency, cost, explainability, governance, security, scalability, and business risk.
- Deep expertise integrating AI solutions with enterprise platforms, knowledge sources, RESTful APIs, event-driven architectures, identity systems, and cloud ecosystems.
- Strong background designing real-time enterprise solutions that account for voice and digital latency, throughput, secure data access, reliability, and system scalability.
- Demonstrated expertise defining AI evaluation, governance, and observability strategies spanning testing, quality, accuracy, safety, drift, and auditability.
- Practical experience with prompt design, context management, RAG, and AI workflow optimization.
- Proven ability to create and deliver compelling technical demonstrations, prototypes, and presentations connecting architecture decisions to business value.
- Demonstrated success partnering with sales teams on technical discovery and AI-focused solution design.
- Strong executive communication, storytelling, and presence with ability to influence senior technical stakeholders.
Responsibilities
- Architect production-ready AI systems for customer experience use cases that combine LLMs, deterministic workflows, tools, orchestration layers, human handoffs, fallback strategies, and failure handling.
- Design scalable RAG and enterprise knowledge architectures to improve response accuracy, relevance, and freshness while balancing latency, performance, security, and governance requirements.
- Establish AI evaluation and observability frameworks that connect accuracy, retrieval quality, tool-call performance, containment, customer satisfaction, safety, drift, cost, and other technical measures to customer and business outcomes.
- Engineer contextual AI experiences that use real-time customer data, interaction history, conversation state, and external signals to deliver coherent and personalized experiences across channels and touchpoints.
- Drive strategic presales engagements through technical discovery, solution architecture, product demonstrations, sandbox and trial engagements, AI integration guidance, and value assessments.
- Develop and validate AI prototypes through production pilot readiness, partnering with account teams and Professional Services to prove use cases and integrations.
- Influence AI product and go-to-market direction by translating customer requirements, implementation insights, and field feedback into actionable guidance for Product Management and Engineering.
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