AI Engineering Lead

🔥 2 minutes ago

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

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 end-to-end project delivery with clear governance and strong stakeholder communication • Mentor junior engineers and contribute to proposals and new business initiatives • Define what AI systems should and should not attempt, and communicate risks and tradeoffs transparently to clients • Design and build production-ready RAG systems, agentic frameworks, and LLM-powered solutions • Apply advanced prompt engineering techniques, including instruction design, few-shot sets, structured outputs, and tool/agent prompts • Lead feasibility assessments across prompting, RAG, fine-tuning, and classical ML • Design evaluation frameworks using LLM-as-a-judge methods, custom metrics, and go/no-go gates • Run structured experiments across prompts, retrievers, chunking strategies, and models • Identify and categorize model failure modes, including hallucinations, retrieval misses, and instruction-following errors • Build scalable inference infrastructure and CI/CD pipelines for AI/ML models • Automate the MLOps/LLMOps lifecycle, including tracking, versioning, deployment, monitoring, and retraining • Design APIs, microservices, and orchestration layers optimized for latency, cost, and reliability

🎯 Requirements

• Expert-level Python • Strong Git practices • Experience with ML/LLM versioning • Solid cloud experience across AWS, Azure, or GCP; Azure preferred • Containerization and orchestration experience • Hands-on RAG experience covering chunking, embeddings, retrieval, reranking, and evaluation • Proven MLOps/LLMOps experience using MLflow, Weights & Biases, or similar tools • Practical evaluation design skills, including metrics, dataset curation, and structured experimentation • Experience with event-driven architectures, APIs, and microservices • Strong communication skills with engineering teams and senior stakeholders • Advanced English required for effective communication with global teams • 6+ years of experience building and deploying AI solutions in production environments • Preferred experience with Databricks MLOps, LLM fine-tuning, agentic GenAI systems, Infrastructure as Code, security and observability for AI services, classical ML, and open-source contributions

🏖️ 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 your location in LATAM