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Software Solution Architect

Axelon

Irvine, CA

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JOB DETAILS
SALARY
$1–$74 Per Hour
SKILLS
Amazon Web Services (AWS), Application Programming Interface (API), Architectural Services, Artificial Intelligence (AI), Automation, Automation Systems, Cloud Computing, Continuous Deployment/Delivery, Continuous Integration, Data Science, Editing, Environmental Management, Leadership, Offshoring, Product Marketing, Production Systems, Python Programming/Scripting Language, Requirements Management, Sales Pipeline, Scalable System Development, Software Architecture, Software Engineering, System Integration (SI)
LOCATION
Irvine, CA
POSTED
8 days ago

Location: 2-3 days/week in the company’s Irvine office, 1 day in downtown LA office, 1 day remote
Work Mode: Hybrid

Responsibilities:

  • Design and develop scalable AI/ML pipelines and intelligent applications aligned with enterprise standards
  • Build agent-based AI workflows, automation systems, and retrieval-based architectures (RAG, vector search, embeddings)
  • Architect and implement LLM orchestration layers supporting content ideation, drafting, and editing workflows
  • Lead integration of AI solutions with backend systems and enterprise platforms (APIs, internal tools, data platforms)
  • Partner with product, marketing, and business stakeholders to translate requirements into AI-driven solutions
  • Provide architectural leadership, guide offshore teams, and ensure delivery aligned with scalability, security, and governance standards

Requirements:

  • At least 8 years of experience in AI/ML, Data Science, or Software Engineering
  • Strong Python backend development experience
  • Hands-on experience with LLM-enabled applications and Generative AI
  • Experience building agent-based/agent-oriented AI systems
  • Strong expertise in retrieval-based systems (RAG, vector databases, embeddings, indexing)
  • Experience with API development and backend system integration
  • AWS cloud-native development experience
  • Experience with CI/CD pipelines and environment management
  • Strong understanding of observability (logging, monitoring, tracing)
  • Experience deploying ML models in production environments
  • Exposure to enterprise AI workflows, automation, and governance models

About the Company

A

Axelon