Company Description 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 a to contribute to our next level of growth and expansion. Job Description We’re seeking an AI Engineering Manager with deep technical expertise in applied machine learning, LLMs, and agentic system design, combined with a strong track record of engineering leadership. In this role, you will be responsible for both driving the architecture and delivery of cutting-edge AI systems—including RAG pipelines and autonomous agents—and leading a team of engineers, fostering growth, collaboration, and technical excellence. You will collaborate closely with Data Science, Product, and Engineering teams to translate ambitious AI concepts into robust, scalable, cloud-native solutions. As a manager, you’ll own delivery outcomes, mentor your team, and help shape the direction of our applied AI capabilities. Key Responsibilities & Skills AI System Architecture & Delivery - Lead the design and implementation of end-to-end AI systems, including GenAI solutions, RAG pipelines, and agentic workflows. - Architect reasoning frameworks and LLM-based automation, including prompt engineering and multi-agent orchestration. - Integrate AI frameworks such as LangChain, LlamaIndex, CrewAI, and LangGraph. - Ensure high-quality, maintainable, and scalable codebases using Python and containerized environments. - Build and maintain robust evaluation pipelines to measure grounding, factuality, performance, cost, and latency. - Define and enforce AI governance strategies: guardrails, output validation, and responsible agent behavior. Engineering Excellence & MLOps - Apply MLOps and software engineering best practices across the full lifecycle — from experimentation to production. - Ensure robust CI/CD pipelines, testing, and observability across cloud platforms (AWS, Azure, GCP). - Oversee the development of APIs and pipelines for batch and real-time inference in production environments. - Maintain high standards of code quality, architecture, and documentation across the team. People Management & Technical Leadership - Manage and grow a team of engineers, supporting career development, performance reviews, and goal setting. - Provide regular coaching and mentorship to both junior and senior engineers. - Facilitate effective feedback, handle difficult conversations constructively, and foster a culture of psychological safety. - Lead project planning, scope definition, and resource allocation across multiple AI initiatives. - Coordinate delivery timelines, dependencies, and milestones in alignment with product and business goals. - Own client relationships for small to mid-sized accounts and ensure successful, referenceable project outcomes. Cross-Functional Collaboration & Communication - Work closely with product managers, data scientists, and stakeholders to align technical execution with strategic objectives. - Communicate complex technical topics to non-technical stakeholders clearly and confidently. - Contribute to organizational AI strategy, hiring decisions, and roadmap planning. - Excellent English communication skills (written and verbal) are essential for working with global teams and clients. Qualifications Must-Have - 7+ years of experience in AI/ML engineering, including at least 2 years in a team or people management role. - Proven track record of building and deploying LLM-powered or GenAI systems in production. - Strong proficiency in Python and familiarity with orchestration libraries like LangChain, CrewAI, and LangGraph. - Deep understanding of agentic architectures, RAG systems, and prompt engineering. - Experience managing engineering teams and delivering multiple concurrent projects on time. - Hands-on experience with CI/CD, MLOps practices, and cloud platforms (AWS, Azure, or GCP). Nice-to-Have - Experience with Snowflake, Snowpark Container Services and Snowflake Cortex. - Background in LLM evaluation frameworks and safety practices. - Prior ownership of client relationships or consulting engagements. Additional Information 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. 👩🏫 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.