Senior AI Engineering Lead

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Vanigent

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2021

💼 Consulting

🏥 Healthcare

💊 Pharmaceuticals

Consulting • Healthcare • Pharmaceuticals

Vanigent is an independent Contract Sales Organization (CSO) specializing in commercial sales execution and support for the pharmaceutical and biopharmaceutical industry. The company's tenured executives deliver field deployment, sales planning and operations, product positioning, and pricing strategies throughout product lifecycles, focusing on rapid implementation, measurable performance, compliance, and talent development to improve patient outcomes and client results.

📋 Description

• Drive the design, development, and deployment of advanced artificial intelligence solutions • Lead AI strategy execution and guide a team of AI and software developers • Develop custom AI solutions including predictive modeling, RAG systems, and agentic AI workflows • Ensure AI systems are scalable, reliable, and aligned with business requirements • Manage AI and software developers, providing coaching and technical guidance • Partner with product and engineering leaders to identify high-value AI opportunities

🎯 Requirements

• 5+ years of experience in Software Development • 3+ years of experience in AI / ML Engineering in Production • 2+ years of experience in LLM / Generative AI Development • 2+ years of experience in Cloud AI Deployment • 2+ years of experience in MLOps / Model Lifecycle Management • 2+ years of People Management / Technical Leadership • Strong proficiency in Python • Working knowledge of TypeScript or JavaScript • Strong experience with PyTorch, TensorFlow, scikit-learn, and Hugging Face Transformers • Hands-on experience with RAG architecture, embeddings, semantic search, vector databases, hybrid retrieval, re-ranking, and graph-augmented retrieval • Experience with LangChain, LangGraph, LlamaIndex, OpenAI SDK, Anthropic SDK, and Model Context Protocol or MCP • Experience with vector databases such as Pinecone, Weaviate, pgvector, ChromaDB, or Qdrant • Experience with fine-tuning techniques such as LoRA, QLoRA, RLHF, and DPO • Strong understanding of MLOps, CI/CD, Docker, Kubernetes, model serving, monitoring, and model versioning • Experience with cloud platforms such as AWS, GCP, or Azure • Strong knowledge of databases, data pipelines, SQL, NoSQL, preprocessing, testing, Git, and software engineering best practices.

🏖️ Benefits

• Paid time off • Flexible work arrangements • Professional development