2 дня назад
Senior Principal Architect, Applied AI Enterprise
172 630 - 258 950$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior Principal Architect, Applied AI Enterprise (Agentic AI/Cloud AI): Designing and deploying enterprise AI-powered solutions with an accent on agentic systems, multi-cloud architecture, orchestration, and MLOps. Focus on building production AI agent systems, integrating tools and data retrieval patterns, evaluating emerging frameworks, and translating business requirements into scalable architecture.
Location: Onsite five days a week in Irving, TX; Peoria, IL; or Broomfield, CO, United States. Relocation is available. Visa sponsorship is not available.
Salary: $172,630–$258,950 per year
Company
is a Fortune 100 manufacturer of construction and mining equipment, engines, turbines, locomotives, and related services.
What you will do
- Develop architecture deliverables for business problems using agentic AI systems and patterns.
- Design technical infrastructure for AI applications, including orchestration layers, tool integrations, data retrieval, and testing.
- Lead the evaluation and deployment of emerging AI technologies and frameworks.
- Translate business requirements into AI solution designs and collaborate with IT, business functions, and product teams.
- Shape scalable, enterprise-wide AI architecture and contribute to 's AI strategy.
Requirements
- Deep knowledge of modern AI/ML architectures, including transformer models, RAG, agent frameworks, and model orchestration.
- Hands-on experience with Azure OpenAI Service, AWS Bedrock, and Google Vertex AI, including multi-cloud or hybrid solutions.
- Expertise in requirements analysis, data architecture, target architecture, and technical roadmap development.
- Strong MLOps knowledge covering model versioning, deployment pipelines, monitoring, and governance.
- Experience with agentic AI systems, multi-agent architectures, tool use, and orchestration frameworks such as LangChain, LangGraph, or Semantic Kernel.
- Software engineering experience with APIs, authentication and authorization, enterprise integration, LLM deployment, RAG, function calling, and context engineering.
Nice to have
- Experience evaluating vector databases, embedding models, orchestration layers, and observability tools.
- Experience with MLOps or LLMOps practices and production AI systems at scale.
- Ability to explain complex technical concepts to non-technical stakeholders and influence architecture decisions.
Culture & Benefits
- Career development and opportunities to work with emerging technologies.
- Medical, dental, and vision benefits, paid time off, and parental and adoption benefits.
- 401(k), HSA, FSA, life insurance, disability benefits, and employee assistance programs.
- Tuition reimbursement, wellness programs, voluntary benefits, and employee discounts.
- Incentive bonus opportunities.
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