Staff Software Engineer, OpenAsset

• 7+ years of professional experience as a backend or full stack engineer, with deep expertise in backend systems
• Deep understanding of LLM technologies, prompt engineering, and fine-tuning approaches
• Experience with AI/ML pipelines, especially retrieval-augmented generation (RAG) and vector databases (e.g., Pinecone, FAISS, Weaviate)
• Proficiency in Python and at least one other backend language (Java, TypeScript, etc.)
• Expertise in cloud platforms (AWS preferred), microservices, and infrastructure as code (Terraform, Docker)
• Strong track record of owning and delivering large-scale backend platforms or internal systems
• Strong knowledge of SaaS integrations and API development (REST, GraphQL)
• Excellent communication skills; able to translate technical work into business value and collaborate across teams

Desirable

• We’re seeking a Staff Software Engineer – AI/ML (Business Systems Intelligence) to take ownership of our internal AI infrastructure and lead our newly formed AI Engineering Pod
• This is a hands-on backend role where you’ll design, implement, and scale AI-powered systems that connect enterprise SaaS data (Salesforce, Gong, Mixpanel, and more) with ChatGPT-5 and future AI models
• You’ll be the point person and technical lead for this team, setting the standard for engineering excellence, building RAG (Retrieval Augmented Generation) pipelines, and enabling AI capabilities across the company
• Beyond building systems, you’ll drive strategy, internal enablement, and mentor engineers as we expand our use of AI for business intelligence and automation
• This is a foundational role with high visibility and impact: you will own the internal AI platform that makes enterprise data accessible, actionable, and intelligent
• Own the design, architecture, and delivery of internal AI/ML systems for business intelligence
• Lead the planning, estimation, and execution of backend and AI/ML projects, ensuring scalable, secure, and reliable systems
• Act as the point person for the AI Engineering Pod, representing the team across Engineering, Product, and Leadership
• Build and maintain APIs, microservices, and data pipelines that enable LLM-powered tools to access and act on SaaS data
• Implement retrieval-augmented generation (RAG) pipelines with vector databases for context-aware AI
• Ensure strong backend foundations: scalability, observability, and maintainability
• Design and deploy AI-enabled internal products that expand company capabilities (e.g. intelligent assistants, automated insights, cross-SaaS workflows)
• Own the internal AI enablement platform, providing reusable tools, frameworks, and APIs for other engineers and business teams
• Partner with stakeholders to identify high-value internal use cases and deliver tailored AI solutions
• Establish best practices for AI/ML development, deployment, and monitoring within internal systems
• Mentor AI Application Engineers and other team members, guiding them on backend, API, and AI/ML integration patterns
• Champion a culture of reliability, documentation, and continuous improvement
• Be the owner-lead for all internal AI/ML systems built by this team, accountable for uptime, performance, and compliance
• Ensure all systems adhere to security, privacy, and compliance standards