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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Lead, AI Engineer (Dublin, CA or USA Remote) - **Company:** Savvymoney, Inc. - **Location:** Dublin, CA, United States (Remote available) - **Experience:** Expert - **Salary:** $150,000.0 - $175,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Code Review, Cyber Security, Computer Literacy, Cursor (Graphical User Interface Elements), DevOps, Python (Programming Language), Software Engineering, Large Language Models, GPT - **Published:** August 10, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=59e1cc78debc383a ## About the Role * 5+ years of professional software engineering experience, including production LLM systems you personally architected and shipped. * Deep hands-on proficiency in Python and cloud-native AWS development, with strong opinions on evals, cost-per-outcome, latency, and prompt-injection defense. * Deep technical literacy with modern AI tools (Copilot, Cursor, Claude, Glean, ChatGPT) - you use them daily, not just demo them. * Strong analytical mindset with experience defining adoption metrics, instrumenting telemetry, and reporting to executive audiences. * Excellent written and verbal communication - you can run a requirements session with a business team and present the outcome to the executive team in the same week. * Demonstrated success driving organization-wide behavior change and running a champions network or community of practice at scale (500+ employees). * Comfort working cross-functionally with engineering, legal, security, HR, and business leadership. Preferred Experience * Fintech, lending, or financial services background. * Prior experience in InfoSec, DevOps, or a regulated-industry technical function - the policy-and-telemetry muscle translates directly. * PE-portfolio company experience. * Experience with AI governance frameworks (NIST AI RMF, ISO 42001, or equivalent). * Bachelor's degree in a relevant field, or compelling self-taught equivalent. ## Description Hands-On Build and Technical Direction * Own the technical direction of every internal AI system we run, and write a large share of it yourself. * Define the reference architectures the whole company builds on - RAG pipelines, agent loops, evals, the LLM gateway, observability, and cost control - and prototype the first working version of each. * Ship production systems end-to-end with the AI Engineer: requirements, prototype, deploy, instrument, iterate. * Set the technical bar by example - code review, eval coverage, prompt-injection defense, and cost-per-outcome discipline. Stakeholder Partnership and Delivery * Run intake with business and executive stakeholders - elicit requirements, pressure-test the use case, and decide what the team builds, buys, or declines. * Own the acceptance gate: the stakeholder who requested the work confirms it in UAT before it ships. * Present outcomes to the people who fund and use them - monthly executive review, quarterly business reviews, and demos to the teams whose work changes. Champions Program and Community * Recruit, train, and run a network of named "AI champions" - at least one per business unit - who serve as distributed sensors and accelerators for adoption. * Run the champions cadence - monthly sync, quarterly offsite, recognition tied to measured impact - and the internal community of practice that shares wins, patterns, and friction across teams. Training and Literacy * Design and deploy a scalable AI literacy curriculum with role-specific tracks for engineering, customer success, finance, legal, sales, recruiting, and partner ops. * Own build-vs-buy on training vendors and certification pathways, and grow a measurable AI-fluency baseline quarter over quarter. Communications and Storytelling * Own the internal AI Slack channel, monthly newsletter, quarterly town halls, and a success-story library tied to dollarized outcomes - translating complex AI concepts into narratives that land with technical and executive audiences alike. Office Hours and Friction Removal * Run weekly drop-in office hours that make the AI Engineering Team's tools and support accessible to every team. * Identify recurring friction (policy ambiguity, tool gaps, integration blockers) and partner with your AI Engineer and the VP, Information Security & DevOps to remove it. Adoption Telemetry * Own the data: % active users by team, by tool, by role. * Identify dark spots and design targeted interventions- such as training, champion deployment, leadership nudges, or licensing changes. * Report adoption metrics into the monthly executive review and quarterly PSG scorecard. Policy Rollout and Tool Licensing * When the AI Engineering Team ships an acceptable-use policy or adopts a new tool, you own getting it adopted in practice - not just published. * Advise on which seats go where, based on adoption data and ROI signals rather than headcount. Partner Ops Enablement * Extend the champions and training model to partner ops teams where ROI clearly exceeds the cost of a custom build. * Coordinate with our partner-facing teams to surface AI use cases that scale across our 1,600+ FI relationships. ## Related Videos - [ Evaluating AI models for code comprehension](https://www.wearedevelopers.com/videos/1462-evaluating-ai-models-for-code-comprehension) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Are Code Reviews Worth It? Insights from 16 Years of Review Data](https://www.wearedevelopers.com/videos/1135-are-code-reviews-worth-it-insights-from-16-years-of-review-data) - [Agentic employees in world's most downloaded FinTech app](https://www.wearedevelopers.com/videos/100123-agentic-employees-in-world-s-most-downloaded-fintech-app) - [AI Killed DevOps... What Now? - Lee Faus](https://www.wearedevelopers.com/videos/1759-ai-killed-devops-what-now-lee-faus) - [Streaming AI Responses in Real-Time with SSE in Next.js & NestJS](https://www.wearedevelopers.com/videos/1630-streaming-ai-responses-in-real-time-with-sse-in-next-js-nestjs) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Fully Remote Software Engineer Jobs](https://www.wearedevelopers.com/magazine/447-fully-remote-software-engineer-jobs) - [Dev Digest 137 - AI'm not sure about this](https://www.wearedevelopers.com/magazine/485-dev-digest-137-ai-m-not-sure-about-this) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline)