Software Architect

About the Role

We are seeking a Customer-Facing Software Architect with deep experience in prompt engineering, LLM tuning, and modern RAG (Retrieval-Augmented Generation) architectures. This role will sit at the intersection of customer success, AI strategy, and software architecture—working directly with clients to design intelligent systems tailored to their specific use cases.

You will be a key player in helping customers adopt and succeed with Crowdbotics’ AI-native platform. If you're passionate about using large language models and retrieval systems to solve real-world problems and enjoy being the technical face of a product, we want to hear from you.

Key Responsibilities

• Serve as the primary technical architect and advisor for customers integrating Crowdbotics' platform into their workflows.
  
  
• Lead design and implementation of AI-enabled software solutions with an emphasis on LLM prompt engineering and RAG pipelines.
  
  
• Collaborate closely with product and engineering teams to translate customer needs into technical requirements and architectural decisions.
  
  
• Tailor prompts and retrieval strategies for domain-specific customer applications, ensuring high-quality and contextually accurate model outputs.
  
  
• Guide customers through best practices in AI-native application development, from model selection and fine-tuning to deployment and iteration.
  
  
• Participate in customer calls, solution workshops, and strategic roadmap discussions.
  
  
• Build proof-of-concepts, technical demos, and architecture diagrams to support sales and onboarding efforts.
  
  
• Stay current with advancements in AI development frameworks, open-source tools, and model providers.
  
  

Requirements

• 10+ years of experience in software engineering and 3+ years of experience in software architecture, with recent focus on AI and LLMs and desire to learn new technologies.
  
  
• General understanding of LLM models (OpenAI, Claude, Mistral, etc.), including prompt design, system message tuning, few-shot learning, and grounding techniques.
  
  
• Hands-on experience with RAG frameworks and tools (e.g., LangChain, LlamaIndex, Haystack, Vector DBs).
  
  
• Strong customer-facing skills with the ability to communicate technical concepts clearly to non-technical stakeholders.
  
  
• Deep familiarity with modern AI-enabled software development practices and the full lifecycle from ideation to deployment.
  
  
• Proficiency in Python and experience with modern backend technologies and cloud platforms (e.g., AWS, Azure).
  
  
• Ability to work cross-functionally in a fast-paced, startup environment.
  
  
• Self-motivated, curious, and passionate about helping customers solve complex problems using AI.
  
  

Bonus Points

• Experience in pre-sales engineering, technical account management, or customer success in AI/ML-related fields.
  
  
• Contributions to open-source AI tools or frameworks.
  
  
• Prior experience working with low-code or natural language-driven development platforms.