高级AI工程师
Senior AI Engineer
Blend 是一家领先的 AI 服务提供商，致力于通过数据科学、AI、技术与人才的合力，为客户创造有意义的影响。公司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。公司通过汇聚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
我们正在寻找一位高级 AI 工程师，为公司的下一轮增长和扩张做出贡献。
领导与交付
· 全面负责项目的交付，具备清晰的治理机制、利益相关者沟通以及结果的责任感
· 建设并指导一支高绩效的 AI 工程团队，建立技术标准并培养注重质量和实用性的文化
· 负责提案和新业务计划，定义技术可行性，并向客户清晰地传达风险和权衡
· 明确 AI 系统应与不应尝试的内容，设定现实的期望，并坦诚说明限制
· 进行技术评审和架构评估，以确保项目和团队的高标准
AI 开发
· 指导 RAG 系统、代理框架和 LLM 驱动解决方案的设计与交付，确保其足以用于生产环境
· 领导应用高级提示工程技巧，包括指令设计、少量示例集、结构化输出和工具/代理提示
· 进行可行性评估，选择适合每个问题的方法：提示、RAG、微调或传统机器学习
· 指导工程师进行端到端 AI 系统设计和生产部署实践
评估与质量
· 设计评估框架，包括 LLM 作为评判者的方法、指标创建（如 recall@k、precision@k）和通过/否决门限
· 在提示、检索器、分块策略和模型之间开展结构化实验，基于证据而非直觉
· 建立团队实践，用于识别和分类模型故障，包括幻觉、检索失败和指令遵循错误
· 设定质量标准，确保 AI 系统满足生产环境的可靠性要求
MLOps 与基础设施
· 构建可扩展的推理基础设施和 CI/CD
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 Senior AI Engineer to contribute to our next level of growth and expansion.
Leadership and Delivery
· Lead project delivery end to end, with clear governance, stakeholder communication, and accountability for outcomes
· Build and mentor a high-performing AI engineering team, establishing technical standards and fostering a culture of quality and pragmatism
· Own proposals and new business initiatives, defining technical feasibility and communicating risks and tradeoffs clearly to clients
· Define what AI systems should and should not attempt, setting realistic expectations and being upfront about limitations
· Conduct technical reviews and architectural assessments to maintain high standards across projects and team
AI Development
· Guide the design and delivery of RAG systems, agentic frameworks, and LLM-powered solutions that are robust enough for production
· Lead the application of advanced prompt engineering techniques including instruction design, few-shot sets, structured outputs, and tool/agent prompts
· Run feasibility assessments to choose the right approach for each problem: prompting, RAG, fine-tuning, or classical ML
· Mentor engineers on end-to-end AI system design and production deployment practices
Evaluation and Quality
· Design evaluation frameworks including LLM-as-a-judge approaches, metric creation (recall@k, precision@k), and go/no-go gates
· Lead structured experiments across prompts, retrievers, chunking strategies, and models, grounded in evidence not intuition
· Establish team practices for identifying and categorising model failures including hallucinations, retrieval misses, and instruction-following errors
· Set quality standards that ensure AI systems meet production reliability requirements
MLOps and Infrastructure
· Build scalable inference infrastructure and CI/CD pipelines for AI/ML models that support rapid iteration and reliable deployment
· Automate the full MLOps/LLMOps lifecycle: tracking, versioning, deployment, monitoring, and retraining across the team
· Design APIs, microservices, and orchestration layers optimised for latency, cost, and reliability
· Lead infrastructure decisions that balance technical excellence with business efficiency
What We Are Looking For
· 5+ years building and deploying AI solutions in production environments
· Expert Python proficiency, strong Git practices, and experience with ML/LLM versioning and deployment
· Solid cloud experience across AWS, Azure, or GCP—preference for Azure—plus containerisation and orchestration knowledge
· Hands-on RAG experience covering chunking, embeddings, retrieval, reranking, and evaluation
· Proven MLOps/LLMOps track record using tools like MLflow, Weights and Biases, or similar
· Practical evaluation design skills: metrics, dataset curation, and structured experimentation
· Experience with event-driven architectures, APIs, and microservices
· A clear communicator equally comfortable with engineering teams and senior stakeholders
· Strong hiring and team-building instincts with proven mentoring experience
What about languages?
· English: Advanced (required for effective communication with global teams and client leadership).
How much experience must I have?
5+ years of hands-on AI/ML engineering experience in production environments, with 2+ years of direct team leadership or technical management responsibility.
Nice to Have
· Databricks MLOps platform
· LLM fine-tuning experience
· Building agentic GenAI systems
· Infrastructure as Code
· Security and observability for AI services
· Classical ML background
· Open-source contributions
Our Perks and Benefits:
📚 Learning Opportunities:
· Certifications in AWS (we are AWS Partners), Databricks, and Snowflake
· Access to AI learning paths to stay up to date with the latest technologies
· Study plans, courses, and additional certifications tailored to your role
· Access to Udemy Business, offering thousands of courses to boost your technical and soft skills
· English lessons to support your professional communication
👨🏽💻 Travel opportunities to attend industry conferences and meet clients
👩🏫 Mentoring and Development:
· Career development plans and mentorship programs to help shape your path
🎁 Celebrations & Support:
· Special day rewards to celebrate birthdays, work anniversaries, and other personal milestones
· Company-provided equipment
⚖️ Flexible working options to help you strike the right balance
Other benefits may vary according to your location in LATAM. For detailed information regarding the benefits applicable to your specific location, please consult with one of our recruiters.
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!