AI 工程师经理
AI Engineer Manager
Blend 是一家领先的 AI 服务提供商，致力于通过数据科学、AI、技术和人才的力量，与客户共同创造有意义的影响。我们的使命是激发大胆的愿景，通过无缝结合人类专业知识与人工智能，解决重大挑战。公司通过世界级的人才和数据驱动的战略，为客户解锁价值并推动创新。我们相信，人与 AI 的力量可以对你的世界产生深远影响，为我们的员工和客户创造更有意义的工作和项目。更多信息，请访问 www.blend360.com
我们正在寻找一名 AI 工程经理，为我们的下一轮增长和扩展做出贡献。
这个职位是做什么的？
我们正在寻找一名 AI 工程经理加入我们的拉美团队，远程全职工作。该职位专注于设计、构建和部署可投入生产的 AI 系统，为客户创造实际影响。理想的候选人将参与现代 AI 交付的整个技术栈，包括 RAG 流水线、代理框架、LLM 驱动的解决方案、评估设计以及 MLOps/LLMOps。
该职位需要一位资深的技术负责人，能够领导端到端的交付工作，指导其他工程师，与利益相关者有效沟通，并帮助客户在 AI 系统应该和不应该尝试的内容上做出务实决策。
作为该职位的一部分，您将负责：
· 全流程领导 AI 项目交付，确保清晰的治理、强大的利益相关者沟通和可靠的执行。
· 设计和构建适合生产环境的稳健 RAG 系统、代理框架和 LLM 驱动的解决方案。
· 应用高级提示工程技巧，包括指令设计、少样本提示、结构化输出和工具/代理提示。
· 领导可行性评估，确定正确的技术方案，包括提示、RAG、微调、传统机器学习或混合解决方案。
· 设计 AI 系统的评估框架，包括 LLM 作为评判者、自定义指标、召回率@k、精确度@k 和通过/否决门限。
· 在提示、检索器、分块策略、嵌入方法、重新排序方法和模型之间进行结构化实验。
· 识别和分类模型故障，如幻觉、检索失败、指令遵循错误和质量下降。
· 构建可扩展的推理基础设施和 CI/CD 流水线
查看英文原文
Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. For more information, visit www.blend360.com
We are seeking an AI Engineer Manager to contribute to our next level of growth and expansion.
What is this position about?
We are looking for an AI Engineer Manager to join our LATAM team in a remote, full-time role. This position is focused on designing, building, and deploying production-ready AI systems that create meaningful impact for our clients. The ideal candidate will work across the full stack of modern AI delivery, including RAG pipelines, agentic frameworks, LLM-powered solutions, evaluation design, and MLOps/LLMOps.
This role requires a senior technical voice who can lead end-to-end delivery, mentor other engineers, communicate effectively with stakeholders, and help clients make pragmatic decisions about what AI systems should and should not attempt.
As part of this role, you will be responsible for:
· Leading AI project delivery end to end, ensuring clear governance, strong stakeholder communication, and reliable execution.
· Designing and building robust RAG systems, agentic frameworks, and LLM-powered solutions suitable for production environments.
· Applying advanced prompt engineering techniques, including instruction design, few-shot prompting, structured outputs, and tool/agent prompts.
· Leading feasibility assessments to determine the right technical approach, including prompting, RAG, fine-tuning, classical ML, or hybrid solutions.
· Designing evaluation frameworks for AI systems, including LLM-as-a-judge, custom metrics, recall@k, precision@k, and go/no-go gates.
· Running structured experiments across prompts, retrievers, chunking strategies, embeddings, reranking approaches, and models.
· Identifying and categorizing model failures such as hallucinations, retrieval misses, instruction-following errors, and quality regressions.
· Building scalable inference infrastructure and CI/CD pipelines for AI and ML models.
· Automating the MLOps/LLMOps lifecycle, including tracking, versioning, deployment, monitoring, retraining, and continuous improvement.
· Designing APIs, microservices, and orchestration layers optimized for latency, cost, reliability, and scalability.
· Mentoring junior engineers and contributing to proposals, solution design, and new business initiatives.
The ideal candidate should have:
· 6+ years of experience building and deploying AI, ML, or data-driven solutions in production environments.
· Strong expertise in Python and solid Git practices.
· Hands-on experience with LLM-powered solutions, RAG systems, and modern GenAI development patterns.
· Practical experience with RAG components, including chunking, embeddings, retrieval, reranking, and evaluation.
· Strong understanding of prompt engineering techniques, including structured outputs, few-shot prompting, instruction design, and tool/agent prompts.
· Proven experience designing evaluation strategies for AI systems, including metrics, dataset curation, structured experimentation, and quality gates.
· Experience with MLOps/LLMOps practices and tools such as MLflow, Weights & Biases, or similar platforms.
· Solid cloud experience with AWS, Azure, or GCP. Azure experience is preferred.
· Experience with containerization, orchestration, scalable inference, APIs, and microservices.
· Understanding of event-driven architectures and production-grade engineering practices.
· Ability to communicate clearly with engineering teams, senior stakeholders, and clients.
· A pragmatic approach to AI delivery, balancing innovation, reliability, cost, latency, and business value.
Nice to have:
· Experience with Databricks MLOps platform.
· Experience with LLM fine-tuning.
· Experience building agentic GenAI systems.
· Experience with Infrastructure as Code.
· Knowledge of security and observability practices for AI services.
· Background in classical machine learning.
· Open-source contributions or public technical work.
What about languages?
Advanced English level is required for written and verbal communication.
How much experience must I have?
At least 6 years of professional experience building and deploying AI, ML, or software solutions in production environments.
Our perks and benefits:
🍔 Every day lunches! (headquarters):
· Vegetarian, vegan, gluten and sugar free options.
· Gourmet meals every Friday with our on-site chef!
⚖️ Flexible working options to help you strike the right balance.
👨🏽💻 All the equipment you need to harness your talent (Macbook and accessories).
☕ Snacks and beverages available everyday (headquarters).
🎮 After office events, football, tennis and game nights (headquarters).
⚽️ Everyone is welcome to join our football league every Wednesday’s and Friday’s.
Challenge your teammates to a pool game and win the office’s trophy! Tennis courts available for friendly matches.
Not a sports person? Don’t worry, we also have chess championships, game and music nights for you to join!
📚 Learning opportunities:
· AWS Certifications (we are AWS Partners).
· Study plans, courses and other certifications.
· English Lessons.
· Learn from your teammates on our Tech Tuesdays!
👩🏫 Mentoring and Development opportunities to shape your career path.
🎁 Anniversary and birthday gifts.
🏡 Great location and even greater teammates!
So what are the next steps?
Our team is eager to learn about you! Send us your resume or LinkedIn profile below and we’ll explore working together!