Own the reliability, observability, evaluation, and production performance of the AI systems powering inclusive finance across emerging markets.
At Boost, we build the AI infrastructure powering digital onboarding for banks and microfinance institutions across Southeast Asia. We enable financial institutions to onboard clients digitally for loans and savings in 5–10 minutes — through chat, without app downloads.
Traditionally, banking meant physical branches and long forms. Boost turns that on its head — with chat-based lending, document AI, and agentic workflows that make financial services 100x faster and radically more accessible. We integrate with a new partner bank in 2–3 weeks, helping them expand their reach instantly.
Backed by top-tier institutional and angel investors, Boost is building the digital rails for inclusive finance in emerging markets.
We're looking for an AI Reliability Engineer to own the reliability, observability, evaluation, and production performance of AI systems — making sure agents and workflows are measurable, reliable, cost-efficient, and production-ready.
This is not a pure ML research role, and it's not a traditional DevOps role. You'll sit between AI Engineering and Infrastructure. You should be comfortable debugging a Kubernetes deployment one hour and designing an LLM evaluation framework the next.
By the end of your first three months, you will have:
Established baseline reliability metrics for our AI systems.
Implemented automated evaluation pipelines for core AI workflows.
Built monitoring dashboards covering quality, latency, and cost.
Defined AI-specific SLOs and incident response procedures.
Reduced production failures and improved deployment confidence.
Created repeatable benchmarks that let us measure progress objectively.
It's an AI Reliability Engineer role that owns the reliability, observability, evaluation, and production performance of Boost Capital's AI systems. You sit between AI Engineering and Infrastructure — making AI applications, agents, and workflows measurable, reliable, cost-efficient, and production-ready. It is neither a pure ML research role nor a traditional DevOps role.
We strongly prefer 3+ years in Site Reliability, Platform, DevOps, or Infrastructure Engineering, strong Python, and experience with Kubernetes, Docker, and Terraform. AI experience matters too: building or deploying LLM-powered applications, prompt engineering, evaluation frameworks such as LangSmith, Braintrust, Weights & Biases, Arize, or Patronus, and understanding of RAG systems, AI agents, and tool calling.
Yes — it's a remote (telecommute) full-time role open to candidates in the United Kingdom, France, the Philippines, Vietnam, and Thailand.
USD 25,000–65,000 per year, based on experience.
Submit your LinkedIn and GitHub using the application form below. You can also email carlo@boostcapital.io or connect on LinkedIn and message directly.
Boost Capital builds the AI infrastructure powering digital onboarding for banks and microfinance institutions across Southeast Asia — enabling financial institutions to onboard clients for loans and savings in 5–10 minutes through chat, without app downloads, using chat-based lending, document AI, and agentic workflows. Boost integrates with a new partner bank in 2–3 weeks.
No cover letter, no long form. Drop your LinkedIn and GitHub and we'll take it from there. We read every application.
Thanks — we've got your LinkedIn and GitHub. If there's a fit, we'll reach out by email.