Lead - AI Engineering

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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

• Translate business needs into testable GenAI and Agentic Engineering solutions with clear outputs and measurable success criteria • Define scope boundaries, risks, and what systems should not attempt • Run feasibility assessments to select prompting, RAG, fine-tuning, or classical ML approaches • Select and develop models based on task requirements, latency, cost, and risk profile • Design prompting strategies including instruction design, few-shot sets, structured outputs, tool/agent prompts, and robustness patterns • Build MVPs and iterate based on evaluation results • Establish prompt iteration methodology with prompt versioning, ablations, and change control • Define evaluation plans for GenAI systems and agentic workflows, including LLM-as-judge evaluation and fairness/bias considerations • Define acceptance thresholds and release gates tied to evaluation metrics • Run structured experiments across prompts, retrievers, chunking, and models • Identify model failures including hallucinations, retrieval misses, instruction-following errors, and formatting failures • Recommend evidence-based improvements with expected lift and trade-offs • Deliver engineering-ready handoffs including prompt packages, RAG configuration, tool schemas, evaluation harnesses, datasets/ground truth, metric definitions, and go/no-go gates • Design scalable and secure Agentic AI architectures following data engineering, MLOps, and LLMOps best practices • Partner with AI Engineering, DS/analysts, Product, Software Engineering, DevOps/Platform Engineering, and Data Engineering teams • Mentor data scientists and analysts on GenAI evaluation methods, labeling operations, and scientific rigor

🎯 Requirements

• 5–10 years of overall AI/ML experience • At least 2–3 years of Generative AI solutions experience • Strong background in applied ML, data science, LLM, and Agentic AI Engineering systems • Demonstrated delivery and client-facing experience • Deep expertise in evaluation design, metrics, and dataset curation for LLM systems • Proven experience in model selection and prompt engineering, including structured output and tool-use prompting • Strong proficiency in Python and major ML frameworks including PyTorch, TensorFlow, and Scikit-learn • Strong experience in LLM fine-tuning, RAG Context Engineering, Claude Code, OpenAI Codex, and Agentic Workflows • Strong RAG design knowledge including chunking, embeddings, retrieval strategies, reranking, and evaluation • Must have implemented Agentic AI SDLC • Experience with GenAI on Azure, AWS, or Snowflake, including Azure OpenAI, AWS Bedrock, or Snowflake Cortex • Experience with vibe coding tools such as AntiGravity, Cursor, and VS Code is highly desirable • Proven ability to build end-to-end GenAI MVPs in Python and prepare them for production handoff • Excellent communication and stakeholder management skills with a strategic mindset

🏖️ Benefits

• Competitive salary • Dynamic career growth opportunities • Tools, mentorship, and experiences for career development • Idea Tanks for pitching, experimenting, and collaborating on ideas • Growth Chats for learning and skill development • Snack Zone with a variety of snacks • Recognition and rewards program, including Hive-Fives and shoutouts • Company-sponsored certifications in AI, Data Science, Cloud, and Analytics technologies