Head of AI Engineering
Yuno
full-time
Posted on:
Location Type: Remote
Location: Colombia
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Job Level
About the role
- Define the AI vision and multi-quarter roadmap aligned with Yuno’s business priorities (product, operations, revenue).
- Build and lead a high-performing AI engineering team: hiring, mentoring, performance management, and career development.
- Establish engineering standards for quality, security, observability, evaluation, and responsible AI.
- Architect and oversee delivery of LLM-powered applications that augment and automate key workflows across Yuno — from customer-facing product capabilities to internal agentic workflows.
- Design autonomous AI systems that can execute technical analysis, testing, troubleshooting, and decision-making at scale.
- Partner with Product to define success metrics and ensure AI initiatives drive measurable business impact.
- Identify high-leverage areas where AI can reduce manual work, optimize processes, and increase organizational intelligence.
- Build systems that enable Yuno to scale without exponential growth in headcount (automation-first, agent-first workflows).
- Lead fine-tuning, contextual optimization, and evaluation of AI systems using Yuno’s proprietary data.
- Build feedback loops, observability metrics, and experimentation frameworks to continuously improve performance.
- Ensure adherence to privacy, compliance, and ethical AI principles across the AI stack.
- Work closely with Engineering, Data, Security, and Infrastructure to build shared AI platform capabilities (retrieval, model serving, tooling, evaluation).
- Drive adoption of AI across the company by enabling other teams with reusable components, templates, and best practices.
- Stay ahead of emerging AI technologies and translate them into differentiated capabilities for Yuno.
Requirements
- 8+ years of professional software/AI engineering experience, with 3+ years focused on LLMs, RAG, or agentic systems in production.
- Demonstrated experience leading teams (hiring, mentoring, delivery management) and owning end-to-end outcomes.
- Strong engineering + product mindset — able to balance technical depth with strategic impact and business priorities.
- Exceptional communication and stakeholder management across Product, Engineering, Data, and Leadership.
- LLMs & RAG: Proven experience designing and deploying RAG pipelines and contextual retrieval systems with models like GPT, Claude, Gemini, etc.
- AI Agents & Multi-Agent Systems: Hands-on experience with frameworks such as CrewAI, LangChain, LangGraph, or similar.
- Fine-Tuning & Context Engineering: Experience with SFT/LoRA or domain adaptation, plus strong evaluation practices.
- Programming & Systems: Strong proficiency in Python (and ideally Go) with production engineering rigor.
- AI Infrastructure: Experience building scalable AI systems in AWS/GCP/Azure, including vector DBs, inference optimization, and model serving.
- Observability & Evaluation: Familiarity with LangSmith, LangFuse, OpenTelemetry/Grafana, or equivalent tooling.
- API Integration: Ability to integrate AI systems with RESTful APIs and internal platforms to ship real product.
- Preferred Qualifications: Experience with LlamaIndex, Hugging Face, and open-source model ecosystems.
- Strong knowledge of embedding strategies, retrieval optimization, and evaluation methodologies.
- Experience with MLOps/CI/CD and production deployment best practices.
- Prior experience in fintech/payments or other regulated, data-intensive industries.
Benefits
- Competitive compensation
- Remote work — work from anywhere
- Home office bonus — one-time allowance
- Work equipment
- Stock options
- Health plan wherever you are
- Flexible days off
- Language, professional, and personal growth courses
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
AI engineeringLLMsRAGagentic systemsfine-tuningcontext engineeringPythonGoMLOpsCI/CD
Soft Skills
team leadershipmentoringcommunicationstakeholder managementstrategic impactperformance managementcareer developmentorganizational intelligenceevaluation practicescross-functional collaboration