Blend360 AI Engineer Manager \\\| SmartRecruiters Google Chrome Microsoft Edge Apple Safari Mozilla Firefox . AI Engineer Manager Full-time 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 Manager AI Engineering to contribute to our next level of growth and expansion. What is this position about? We are looking for a hands-on Senior Manager to lead the design and implementation of advanced AI systems focused on Intelligent Document Processing (IDP) within complex domains such as insurance and construction. This role will drive the ingestion and structuring of highly complex, multi-format documents including lengthy policy and claims files, handwritten notes, scanned images, and construction-related documentation transforming them into structured databases and production-ready AI workflows. The ideal candidate combines strong technical depth in Generative AI with leadership capabilities, helping architect scalable solutions on modern cloud platforms (e.g., Databricks) while mentoring a high-performing AI engineering team. Job Description Architect and lead the development of AI-powered Intelligent Document Processing systems capable of ingesting complex, multi-modal documents (text, scanned PDFs, handwritten content, images, construction diagrams). Design and implement end-to-end pipelines that extract, structure, and store information in scalable databases for downstream analytics and LLM-based applications. Develop and deploy agentic workflows that orchestrate LLM reasoning, computer vision models, OCR systems, and external tools/APIs. Build production-grade solutions leveraging LLM frameworks (e.g., LangChain, LlamaIndex, LangGraph) and language-vision models. Oversee deployment in cloud-based environments (Databricks preferred), ensuring scalability, reliability, and cost efficiency. Lead the design of RAG pipelines and structured knowledge systems to enable accurate retrieval and reasoning over insurance and claims documentation. Collaborate closely with client stakeholders to understand complex document ecosystems (e.g., insurance policies, claims files, construction reports) and translate them into scalable AI architectures. Implement evaluation frameworks and guardrails to ensure model accuracy, factual grounding, compliance, and responsible AI practices. Provide technical leadership and architectural guidance while remaining deeply hands-on in development and prototyping. Mentor and develop AI engineers and data scientists, fostering best practices in applied AI engineering. Qualifications Strong experience designing and deploying Applied AI solutions in production environments. Deep expertise in LLM ecosystems, including prompt engineering, RAG architectures, and agent-based systems. Hands-on experience with Python and AI frameworks such as LangChain, LangGraph, LlamaIndex, or similar. Experience building multi-modal systems combining NLP, OCR, and computer vision for document understanding. Proven experience structuring unstructured and semi-structured data into scalable databases. Strong understanding of cloud-native architectures (Databricks, AWS, Azure, or GCP). Experience working with complex enterprise document workflows (insurance industry experience is highly preferred). Solid understanding of ML lifecycle management, CI/CD, containerization, and scalable API deployment. Strong leadership skills with the ability to guide architecture while staying technically hands-on. Excellent stakeholder communication skills, especially in complex, client-facing environments. What about languages? Advanced English required (strong technical and client-facing communication skills). 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. 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. I'm interested I'm interestedPrivacy Notice ImprintCookies Settings I'm interested Refer a friend share this job Share on LinkedIn Share on Facebook Share on Twitter Share via email Share on Xing Share on WeChat Share to WeChat × Copy the link and open WeChat to share. Copy to clipboard Open WeChat Share to WeChat × Use Scan QR Code in WeChat and click ··· to share. AI Engineer Manager Montevideo, Uruguay Full-time I'm interested I'm interested

The role requires strong experience in designing and deploying Applied AI solutions in production environments. Deep expertise in LLM ecosystems, including prompt engineering, RAG architectures, and agent-based systems, is necessary. Hands-on experience with Python and AI frameworks such as LangChain, LangGraph, or LlamaIndex is essential. Building multi-modal systems that combine NLP, OCR, and computer vision for document understanding is also a requirement. Proven experience in structuring unstructured and semi-structured data into scalable databases is expected. A strong understanding of cloud-native architectures and experience with complex enterprise document workflows, particularly in the insurance industry, is highly preferred. Solid understanding of ML lifecycle management, CI/CD, containerization, and scalable API deployment is needed. Strong leadership skills with the ability to guide architecture while remaining hands-on, alongside excellent stakeholder communication skills, are also required.