• Lead a team of engineers delivering high-quality software for the EHS platform • Responsible for team’s delivery, health, and growth • Stay closely involved with technical work while driving outcomes across the product • Collaborate with Product Management, QA, and peer engineering teams to plan and execute on commitments • Remove blockers and build a team culture of quality, ownership, and continuous improvement • Maintain hands-on involvement with code daily (75% technical role)

• Lead and grow a senior team of engineers building Cribl's dashboards, notebooks, visualizations, investigations, and analytical discovery capabilities • Partner closely with Product to translate vision into execution -- surfacing ideas, shaping direction, and communicating the 'why' to your team with clarity and energy • Drive the team's delivery rhythm across dashboards, notebooks, visualizations, scheduled searches, AI-assisted workflows, and performance improvements that directly shape how customers interact with Cribl Search • Shape technical direction alongside staff+ engineers, ensuring architectural decisions balance speed, quality, and long-term scalability • Mentor and develop engineers at all levels, creating shared ownership and clarity across a technically deep, senior team • Act as a storyteller for the team -- connecting individual work to broader product vision and customer value

Role Description We are looking for an AI Engineer Manager with hands-on experience designing and deploying scalable AI solutions. In this role, you will be part of a cross-functional team working on cutting-edge projects involving Retrieval-Augmented Generation (RAG), agentic frameworks, and end-to-end MLOps workflows. - Design, develop, and deploy AI solutions. - Implement Retrieval-Augmented Generation (RAG) and fine-tuning techniques. - Utilize and integrate AI frameworks like LangChain. - Use advanced prompt engineering techniques to solve complex problems with LLMs. - Build and manage agentic frameworks such as CrewAI and Google ADK. - Apply MLOps best practices to streamline AI development workflows. - Monitor and trace AI applications performance. - Collaborate across teams to ensure alignment with traditional ML and AI methodologies. - Work on end-to-end software engineering for scalable solutions. - Experience in cloud AI services (Azure, AWS, Google Cloud, etc.). - Strong understanding of machine learning concepts and traditional AI concepts. - Experience with MLOps tools and practices (e.g., model deployment, monitoring). - Solid programming skills in Python or other relevant languages. - Excellent problem-solving skills and the ability to work in a collaborative environment. Qualifications - Experience in cloud AI services (Azure, AWS, Google Cloud, etc.). - Strong understanding of machine learning concepts and traditional AI concepts. - Experience with MLOps tools and practices (e.g., model deployment, monitoring). - Solid programming skills in Python or other relevant languages. - Excellent problem-solving skills and the ability to work in a collaborative environment. - Nice to have skills: - Experience Azure is a plus. - Experience with Kubernetes is a plus. - Experience with Google ADK is a plus. - Experience with n8n or Orkes is a plus. - Experience in AI Evaluation is a plus. Requirements - Excellent written and verbal English for clear and effective communication with the team. - At least 5+ years of experience as an AI Engineer or similar. 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.

• Build, lead, and mentor two high-performing engineering teams spanning clustering infrastructure and exposure data systems. • Drive the technical vision and roadmap across both domains, balancing reliability, scalability, cost efficiency, and speed of iteration. • Own the re-architecture of exposure systems to trace funds in real time, combating nation-state actors and darknet markets. • Evolve the next-generation clustering platform, ensuring Chainalysis stays ahead of an ever-changing blockchain landscape. • Partner with data producers, consumers, and product stakeholders to deliver a world-class developer and data science experience. • Establish engineering processes, tooling, and best practices that accelerate your teams and the broader organization. • Dive into hard problems hands-on when needed - architecture decisions, incident response, or unblocking the team. • Champion a culture of quality, correctness, and continuous improvement across mission-critical data systems.