Lead AI Engineer

🔥 5 minutes ago

🇦🇷 Argentina – Remote

⏰ Full Time

🟠 Senior

🤖 AI Engineer

👻 Ghost score 19%

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Logo of Blend360

Blend360

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 • Establish technical standards and foster a culture of quality and pragmatism • Own proposals and new business initiatives, defining technical feasibility and communicating risks and tradeoffs to clients • Define realistic boundaries and expectations 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 advanced prompt engineering, including instruction design, few-shot sets, structured outputs, and tool/agent prompts • Run feasibility assessments across prompting, RAG, fine-tuning, and classical ML • Mentor engineers on AI system design and production deployment • Design evaluation frameworks, including LLM-as-a-judge, recall@k, precision@k, and go/no-go gates • Lead structured experiments across prompts, retrievers, chunking strategies, and models • Establish practices for identifying and categorising model failures • Set AI production reliability standards • 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 for latency, cost, and reliability • Lead infrastructure decisions balancing technical excellence and business efficiency

🎯 Requirements

• 5+ years building and deploying AI solutions in production environments • Expert Python proficiency • Strong Git practices • Experience with ML/LLM versioning and deployment • Solid cloud experience across AWS, Azure, or GCP; preference for Azure • 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 • Clear communication with engineering teams and senior stakeholders • Strong hiring and team-building instincts with proven mentoring experience • English: Advanced (required for effective communication with global teams and client leadership) • 2+ years of direct team leadership or technical management responsibility

🏖️ 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

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