Senior AI Engineer

Welsbach was founded in 2021 with a singular vision: to become Asia's leading bridge between high-growth companies and global capital markets.

Our team of seasoned investment banking professionals, with decades of combined experience at tier-one institutions including Goldman Sachs, JP Morgan, Deutsche Bank, and Macquarie, recognized the critical opportunity in cross-border SPAC and IPO transactions across Asia–West corridors.

Welsbach is hiring for one of our portfolio companies building the AI operating layer for enterprises.

The company focuses on deploying AI agents that execute real business workflows across sales, operations, finance, and customer support — not dashboards or copilots.

Their approach:

• High-value enterprise deployments
• Converted into scalable Agent-as-a-Service (AGaaS) products

This is a senior, high-ownership role focused on building and deploying real-world AI systems.

You will be responsible for taking problems from ideation to production, designing architectures, making key technical decisions, and shipping systems that work reliably in real business environments.

You will define how systems should be built, including model selection, system design, tradeoffs (latency vs cost vs accuracy), and failure handling.

You'll work closely with founders and enterprise clients, translating business problems into scalable AI systems, while setting the technical direction for how agentic workflows are designed and deployed in the company.

• Own end-to-end development of AI systems (design → build → deploy → improve)
• Design and implement multi-agent systems (planning, reasoning, memory, tool orchestration)
• Architect Retrieval-Augmented Generation (RAG) pipelines with strong retrieval quality, evaluation, and iteration loops
• Make decisions on model selection, system design, and architecture tradeoffs
• Integrate AI systems into CRMs, ERPs, internal tools, and external APIs
• Build production-grade systems with logging, monitoring, guardrails, and fallback mechanisms
• Define and implement evaluation frameworks (accuracy, latency, cost, reliability)
• Optimize systems across performance, scalability, and cost
• Handle failure modes (hallucinations, tool errors, edge cases) and improve system robustness
• Work directly with founders and enterprise clients to translate business problems into AI systems
  

• 4–7 years of experience in AI, software engineering, or related fields
• Proven experience building and deploying production systems
• Experience owning features or systems end-to-end
• Master's in Computer Science, AI, Data Science
• Completed relevant AI/ML/LLM-focused courses or certifications
  

• Strong Python skills with backend/system development experience
• Hands-on experience with LLMs (OpenAI, Claude, or other open-source models)
• Deep understanding of:
• Prompting strategies & evaluation
• RAG systems (chunking, retrieval, ranking, caching)
• Agent design patterns & tool usage
• Strong experience with APIs, integrations, and async workflows
• Ability to design systems and make architecture decisions
• Experience building reliable, production-ready systems (not just demos)
• Experience building multi-agent systems in production
• Experience with model optimization / fine-tuning / inference tradeoffs
• Exposure to workflow automation tools (N8N, Zapier, or custom pipelines)
• Understanding of enterprise systems (CRM, ERP, data pipelines)
• Experience handling LLM failure modes, guardrails, and reliability systems
• Must share GitHub / portfolio / project links
• Highlight systems you've built or owned end-to-end
  

• Competitive salary + performance upside
• High ownership as an early team member
• Opportunity to build enterprise-scale AI systems