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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior AI Engineer (Remote) - **Company:** FINOM, INC. - **Location:** United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Fraud Prevention and Detection, Python (Programming Language), Knowledge-Based Systems, NoSQL, Open Source Technology, SQL Databases, Datadog, Pytorch, Large Language Models, Prompt Engineering, Backend, Event Driven Architecture, Containerization, AI Platforms, Kubernetes, HuggingFace, Document Classification, Docker - **Published:** July 29, 2026 - **Apply:** https://arc.dev/remote-jobs/j/redirect/o9aehvpzd6 ## About the Role * A strong software engineer with deep Python experience and a track record of shipping production systems * Comfortable across the full lifecycle: prompting, retrieval, experimentation, evaluation, deployment, and production support * Strong at turning ambiguous business problems into robust technical solutions * Product-minded and focused on real user outcomes, not just model outputs * Autonomous, pragmatic, and able to keep momentum without heavy supervision * Clear in communication and comfortable working across functions * Curious, proactive, low-ego, and biased toward action * Someone who actively keeps up with the fast-moving AI landscape and can separate hype from what is actually useful Must-Haves * Proven experience building and deploying AI systems in production * Strong Python and software engineering fundamentals * Hands-on experience with LLM applications, including some of: RAG, tool use, agents, prompt engineering, evals, structured outputs, guardrails, or fine-tuning * Experience integrating AI systems into backend or product workflows * Ability to design meaningful evaluation, monitoring, and continuous improvement loops * Experience with cloud infrastructure and containerized deployments * Strong ownership mindset and ability to work through ambiguity * Actively experiments with new AI models, tools, and agentic patterns, and can evaluate which approaches are worth productionizing * Strong grasp of the fast-moving AI landscape, with the ability to turn relevant advances into practical product and engineering decisions * Fluent English Nice-to-Haves * Experience in fintech, financial services, risk, compliance, or operations-heavy environments * Experience with applied ML beyond LLMs, such as classification, anomaly detection, ranking, or document intelligence * Experience with vector databases, knowledge systems, and retrieval infrastructure * Experience with model benchmarking, experimentation frameworks, and cost or latency optimization at scale * Background in startups or as a founder * Contributions to open-source or visible side projects in AI Example Tech Stack You do not need experience with every item, but this role will likely involve technologies such as: * Languages: Python, SQL, noSQL * LLM / AI: OpenAI, Anthropic, LangGraph, Hugging Face, Ollama, PyTorch, OpenClaw * Patterns: RAG, tool calling, agent workflows, eval pipelines * Infrastructure: Docker, Kubernetes, AWS / GCP / Azure * Data / Platform: Vector databases, event-driven systems, APIs, observability tooling ## Description At Finom, we're not just redefining the entrepreneurial experience - we're empowering our employees to make a real difference. Your work matters, and your impact extends far beyond product metrics. We nurture innovation and an inspiring work environment where bold ideas thrive, prioritizing thorough research, swift implementation of solutions, and ensuring that every effort we make benefits our users, employees, partners, and our business as a whole. Maintaining our start-up spirit, we prioritize thorough research, swift implementation of solutions, and ensuring that every effort we make benefits our users, employees, partners, and, of course, our business. We are looking for a Senior AI Engineer to design, build, and operate AI systems that solve real business problems across Finom. This role is for someone who can move comfortably from prototype to production: shaping the solution, building the system, measuring quality, and improving it over time. You will work on high-impact initiatives across onboarding, customer support, AI accounting, fraud and risk workflows, document understanding, internal automation, and agentic systems used by multiple teams. This is not a pure research role. It is a hands-on engineering role focused on delivering production-grade AI capabilities that create clear value for customers and the business. What You Will Be Doing * Build and ship AI-powered product and internal solutions using LLMs, RAG, tool calling, workflows, and agentic patterns * Own AI systems end-to-end: problem framing, architecture, implementation, evaluation, deployment, monitoring, and iteration * Partner closely with solution managers, domain teams, and engineers to integrate AI into real workflows rather than isolated demos * Design quality and evaluation frameworks for AI systems, including offline evals, online signals, failure analysis, and continuous improvement loops * Develop scalable and reliable inference pipelines with strong attention to latency, cost, security, and observability * Work on use cases such as onboarding, customer care, transaction and document classification, knowledge assistants, fraud detection, and operational automation * Contribute to AI platform and tooling decisions that improve reuse, speed, and consistency across teams * Challenge assumptions, propose better approaches, and help shape the roadmap rather than only execute tickets * Experiment boldly, learn quickly from failures, and turn insights into stronger systems and better practices What Success Looks Like In your first 6 to 12 months, you will: * Become fully embedded in the team and business domains you support * Deliver at least one significant AI capability into production * Generate visible impact through revenue uplift, cost savings, productivity gains, or risk reduction * Raise the technical bar for how Finom builds, evaluates, and operates AI systems * Help other teams adopt AI more effectively through strong engineering practice and pragmatic guidance ## Related Videos - [Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps](https://www.wearedevelopers.com/videos/1894-shipping-faster-with-less-render-on-cloud-hosting-ai-workloads-and-the-future-of-devops) - [Leveraging Real time data in FSIs](https://www.wearedevelopers.com/videos/806-leveraging-real-time-data-in-fsis) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [Agentic employees in world's most downloaded FinTech app](https://www.wearedevelopers.com/videos/100123-agentic-employees-in-world-s-most-downloaded-fintech-app) - [NoSQL Data Modeling for Front-end Developers](https://www.wearedevelopers.com/videos/297-nosql-data-modeling-for-front-end-developers) ## 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) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Dev Digest 137 - AI'm not sure about this](https://www.wearedevelopers.com/magazine/485-dev-digest-137-ai-m-not-sure-about-this) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it)