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Felix

Applied AI Engineer | L&D

Felix is hiring an Applied AI Engineer | L&D in Guadalajara, Mexico. Level rates it ; you can apply on Felix.

Level's read on this job

  • Works on AI ●●●○ is how Level rates this AI engineer role: the daily work is on AI products, without building the model.
  • Tools and skills the posting cites include OpenAI and RAG.
  • Level lists 92 other open roles at Felix.
  • The role was posted in the last few days.

AI in this role

openai
rag
About Us
At Félix, we are building the indispensable financial companion for Latinos in the US. We combine an AI-powered, conversational-first interface with real-time financial infrastructure to make cross-border money movement as easy as sending a text. Starting with fast, affordable remittances powered by AI and crypto rails, we are expanding into credit, savings, and wallet services to support the complete immigrant financial journey. Our ambition is to deliver a white-glove financial experience with the simplicity of a conversation to a community the traditional financial system has historically overlooked.
We are a hyper-growth Series C company, backed by over $300 million in funding from top-tier global investors, including Andreessen Horowitz, QED, Castle Island, Switch Ventures, HTwenty, Monashees, General Catalyst Customer Value Fund. This isn't just about the numbers; it's a testament to the trust our investors have in our vision and our team. Additionally, Félix was selected as an “Endeavor Entrepreneur” and was a recipient of the CrossTech Fintech Startups Award. 
Joining Félix means you will be part of a team building a legacy, a company that will outlive us all. This is a rare opportunity to apply your skills to a deeply meaningful mission—serving a community that has been underserved for too long because we are obsessed with our customers. We get things done with urgency and focus, driven by extreme ownership over our impact. We collaborate without ego, fostering radical transparency and fierce loyalty so we can grow together. Because we aim for insanely great rather than just good enough, we stay insatiably curious—always experimenting, building the future today, and delivering a product that truly makes our users' lives better.
About the Role
We’re looking for an Applied AI Engineer to help the AI team and colleagues across Félix get more out of AI in their daily work. You’ll build and debug agents and integrations, help colleagues with their own builds, and turn what works into reusable frameworks and learning resources. Success means teams can use AI on their own, solve technical blockers, and keep their AI workflows running day to day.You will combine hands-on engineering with technical office hours, mentoring and role-specific learning programs. Working with team leads and Internal Talent, you will identify skill gaps, track applied learning and follow through after training. You will develop expertise in Maestro and other approved platforms, partner with the AI Solutions Manager on shared practices, and engage FDE, AI Enterprise, Data, Security and platform specialists when deeper support is needed.
Responsibilities
  • Build support: Build and improve reference agents, tool integrations and workflows with Python, LLM SDKs and APIs. Pair with colleagues to scope practical builds, review code, and debug prompts, retrieval, tool calls, state, permissions and failures. Production systems stay with FDEs and specialist engineers.
  • Office hours and escalation: Run regular technical office hours, triage requests and track issues to closure. Escalate complex integration, data, security or production problems with reproducible examples, logs and attempted fixes, and turn recurring issues into resources.
  • Reusable frameworks: Turn shared standards into starter kits, tested agents, integration patterns and troubleshooting guides, with examples for tool calling, data access, evaluations, human review and failure handling. Keep documentation, versioning, permissions and ownership clear on approved platforms, including Maestro, our in-house AI assistant that works across Slack, Notion, Google Workspace and our data.
  • Technical teaching and mentoring: Own the technical content and exercises for hands-on bootcamps and tracks, and teach through live builds and debugging. Mentor colleagues through guided builds and code reviews until they can maintain their own work.
  • Platform expertise and improvement: Keep working expertise in Maestro, other approved tools and data safeguards. Test new capabilities on real tasks, share practical guidance, and bring recurring gaps to platform owners. Track independent task completion, blocker resolution, resource reuse and sustained adoption.

Requirements
  • Applied AI experience: Hands-on experience building LLM applications, agents or automations for real users, including what failed and how you improved it.
  • Engineering and diagnostics: Strong Python, APIs, authentication, Git, testing and debugging, with practical use of at least one LLM SDK such as OpenAI or Google. You can read logs and traces, isolate failures and create reproducible examples.
  • Agents and evaluations: Experience with tool calling, multi-step workflows, state, structured outputs, human review and failure handling. You can build useful evaluations and explain quality, latency, cost and data safeguards.
  • Teaching: Experience mentoring builders and mixed technical and business audiences through live builds and debugging, with follow-through after training. This is tested in the interview with a live pairing or debugging exercise.
  • Collaboration: You turn ambiguous requests into testable hypotheses, know when to escalate, and close the loop.

Nice to have
  • Practical SQL and CI/CD
  • RAG and vector databases
  • Maintainable starter kits or reusable components you have built
  • Experience supporting operations teams


What We Offer


  • Competitive salary
  • Initial stock options grant
  • Annual performance bonus
  • Unlimited PTO
  • Paid parental leave
  • Hybrid work setup 
  • Health, dental, and vision plans 
  • Continuous learning opportunities 
  • Empowering opportunities for growth in a dynamic entrepreneurial environment


Equal Opportunity Employer


At Félix, we are committed to providing equal employment opportunities to all qualified employees and applicants without regard to race, religion, nationality, sex, sexual orientation, gender identity, age, or disability. This policy applies to all terms and conditions of employment, including recruitment, hiring, placement, promotion, training, compensation, benefits, and termination.Want to learn more about our privacy practices? Check out our Privacy Policy.

How we rate this

Applied AI Engineer | L&D at Felix rates 67 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

RAGOpenAI

Also common in AI engineer jobs at this level

Pay

Typical AI engineer job
$184k

This posting doesn't list pay. Use the typical AI engineer figure when pay comes up. See AI engineer jobs

Questions you could be asked

  1. How would you design a retrieval step so the model answers from real data instead of guessing?
  2. Walk me through how you've used OpenAI in your day-to-day work.
  3. Describe a typical day in a role like this one: which parts run through AI directly?
  4. If you removed AI from this role, what would be left, and how do you decide what still needs a human?

Adapt your resume

  • List these exact terms on your resume: RAG and OpenAI. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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