AI Engineering Manager

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Blend360

WebsiteLinkedInAll Job Openings

501 - 1000 employees

🏥 Healthcare

🏨 Hospitality

✈️ Travel

💰 $100M Private Equity Round on 2022-08

Healthcare • Hospitality • Travel

Blend360 is a professional services company specializing in AI, data analytics, and data-driven solutions. They work with Fortune 1000 and large enterprise brands to tackle significant challenges by integrating people and artificial intelligence. Blend360 focuses on several domains including business intelligence, data engineering, data science, MLOps, and data governance. Their industries of expertise encompass financial services, energy, healthcare and life sciences, retail, technology, media & telecom, and travel & hospitality. Blend360 is recognized for their AI and data solutions, having earned accolades such as "AI-Enabling Solution of the Year" and being listed among the "Top Generative AI Service Providers 2024.

📋 Description

• Lead project delivery end to end with governance, stakeholder communication, and accountability for outcomes • Build and mentor a high-performing AI engineering team and establish technical standards • Own proposals and new business initiatives, defining technical feasibility and communicating risks and tradeoffs • Define realistic capabilities and limitations for AI systems • Conduct technical reviews and architectural assessments • Guide design and delivery of production-ready RAG systems, agentic frameworks, and LLM-powered solutions • Lead prompt engineering across instruction design, few-shot sets, structured outputs, and tool or agent prompts • Assess feasibility and select prompting, RAG, fine-tuning, or classical ML approaches • Mentor engineers on AI system design and production deployment • Design evaluation frameworks, metrics, datasets, experiments, and go/no-go gates • Establish practices for identifying and categorising model failures • Set production reliability standards for AI systems • Build scalable inference infrastructure and CI/CD pipelines • Automate the MLOps/LLMOps lifecycle, including tracking, versioning, deployment, monitoring, and retraining • Design APIs, microservices, and orchestration layers optimized for latency, cost, and reliability • Lead infrastructure decisions balancing technical excellence and business efficiency

🎯 Requirements

• 7+ years building and deploying AI solutions in production environments • 2+ years of direct team leadership or technical management experience • Expert Python proficiency • Strong Git practices • Experience with ML/LLM versioning and deployment • Solid cloud experience across AWS, Azure, or GCP, with preference for Azure • Containerisation and orchestration knowledge • Hands-on RAG experience with chunking, embeddings, retrieval, reranking, and evaluation • Proven MLOps/LLMOps experience using MLflow, Weights and Biases, or similar tools • Practical evaluation design skills, including metrics, dataset curation, and structured experimentation • Experience with event-driven architectures, APIs, and microservices • Clear communication with engineering teams and senior stakeholders • Strong hiring and team-building instincts • Proven mentoring experience • Advanced English required for communication with global teams and client leadership

🏖️ Benefits

• Certifications in AWS, Databricks, and Snowflake • Access to AI learning paths • Study plans, courses, and additional certifications tailored to the role • Access to Udemy Business • English lessons • Travel opportunities to attend industry conferences and meet clients • Career development plans and mentorship programs • Special day rewards for birthdays, work anniversaries, and other personal milestones • Company-provided equipment • Flexible working options • Other benefits may vary according to location in LATAM