Lead AI Engineer (LLM & Agents) at Trust Wallet

Job description

About the company Trust Wallet is the secure, self-custody Web3 wallet that empowers people to own and control their digital assets. Whether you're new to crypto or an experienced user, Trust Wallet makes it easier, safer, and more convenient to explore Web3, securely access dApps, manage your crypto, and buy and sell digital assets, all in one place. About the Role We're looking for a Lead AI Engineer to own the backend and Agent systems behind our LLM-powered products. The role is end to end: you'll build the Agent workflows, define how we measure quality, keep them reliable in production, and shape where the product goes next. This role is for someone who has shipped LLM features to real users, stayed with them after launch, and can prove with data that their changes made things better. Job Scope: Build and own AI backend and Agent workflows - Design, build, and maintain multi-turn conversation systems, including context management, tool calling, knowledge retrieval (RAG), state management, and human handoff. Drive evaluation and continuous improvement - Define success criteria with Product, Design, and QA leads. - Turn production failures into evaluation samples and regression tests. - Measure the impact and side effects of every change before and after release. Diagnose problems across the stack - Isolate the root cause of failures: model judgment, knowledge gaps, abnormal tool responses, backend instability, or conflicting rules. - Apply the right fix for each cause rather than defaulting to prompt tweaks. Own production reliability - Handle timeouts, retries, graceful degradation, async jobs, and third-party dependency failures. - Make sure every issue is traceable through logs, every change is versioned, and every failure has a recovery path. Shape product and technical decisions - Give clear, reasoned positions on requirements, covering feasibility, cost, risk, and alternatives. - Propose better approaches and break work into phased, shippable deliverables. Communicate proactively and follow through - Share progress, blockers, ETAs, and next checkpoints without needing to be chased. - After launch, track real-world impact and leave clear documentation and handover materials. Requirements: - Production LLM/Agent experience at scale. You've built LLM or Agent features used by 10,000+ active users, and you've maintained and improved them after launch. - Strong backend engineering fundamentals. You're comfortable owning production code, APIs, data flows, and incident troubleshooting. Experience designing and implement backend services in Golang and integrate with LLMs and AI systems. - Real evaluation discipline. You've built evaluation sets, regression suites, and production monitoring, and you can explain how you confirmed an improvement was real rather than random fluctuation. - Ownership mindset. You make decisions, surface risks early, and don't consider a feature done until it's verified in production. - Web3 experience. Preferably 1 year of experience in a crypto, DeFi, or Web3 company (wallet, exchange, L1/L2 protocol, or DeFi platform strongly preferred) ADDITIONAL INFORMATION This is a global and fully remote role. You must have the right to work for the country you are based. WHY WORK AT TRUST WALLET? - Be a part of the world’s leading blockchain ecosystem that continues to grow. - Excellent learning and career development opportunities. - Work alongside diverse, world-class talent, in an environment where learning and growth opportunities are endless. - Tackle fast-paced, challenging and unique projects. - Work in a truly global organization, with international teams and a flat organizational structure. - Work fully remotely with flexible working hours. - Enjoy competitive salary and benefits. Apply today to join our team in building the world’s most trusted and secure crypto wallet and enable a decentralized future for everyone. Trust Wallet is committed to being an equal opportunity employer. We believe that having a diverse workforce is fundamental to our success. *Due to the large amount of the applications, please consider your application as unsuccessful should you not be contacted within 4 weeks from your application date.

Requirements

Must-haves

This role is for someone who has shipped LLM features to real users, stayed with them after launch, and can prove with data that their changes made things better.
Build and own AI backend and Agent workflows
Design, build, and maintain multi-turn conversation systems, including context management, tool calling, knowledge retrieval (RAG), state management, and human handoff.
Drive evaluation and continuous improvement
Define success criteria with Product, Design, and QA leads.
Turn production failures into evaluation samples and regression tests.
Measure the impact and side effects of every change before and after release.
Diagnose problems across the stack
Isolate the root cause of failures: model judgment, knowledge gaps, abnormal tool responses, backend instability, or conflicting rules.
Apply the right fix for each cause rather than defaulting to prompt tweaks.
Own production reliability
Handle timeouts, retries, graceful degradation, async jobs, and third-party dependency failures.
Make sure every issue is traceable through logs, every change is versioned, and every failure has a recovery path.
Shape product and technical decisions
Give clear, reasoned positions on requirements, covering feasibility, cost, risk, and alternatives.
Propose better approaches and break work into phased, shippable deliverables.
Communicate proactively and follow through
Share progress, blockers, ETAs, and next checkpoints without needing to be chased.
After launch, track real-world impact and leave clear documentation and handover materials.
Production LLM/Agent experience at scale. You've built LLM or Agent features used by 10,000+ active users, and you've maintained and improved them after launch.
Real evaluation discipline. You've built evaluation sets, regression suites, and production monitoring, and you can explain how you confirmed an improvement was real rather than random fluctuation.
Ownership mindset. You make decisions, surface risks early, and don't consider a feature done until it's verified in production.
This is a global and fully remote role. You must have the right to work for the country you are based.

Nice-to-haves

Web3 experience. Preferably 1 year of experience in a crypto, DeFi, or Web3 company (wallet, exchange, L1/L2 protocol, or DeFi platform strongly preferred)

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aillmgolang

Platform: ashby
Effort: quick

Benefits

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