Lead Artificial Intelligence Engineer

About the Company: ProductSquads was founded with a bold mission: to engineer capital efficiency through autonomous AI agents, exceptional engineering, and real-time decision intelligence. We’re building an AI-native platform that redefines how software teams deliver value—whether through code written by humans, agents, or both. Our stack combines agentic AI systems, ML pipelines, and high-performance engineering workflows. This is your chance to build not just models, but systems that think, decide, and act. We’re developing AI fabric tools, domain-intelligent agents, and real-time decision systems to power the next generation of product delivery.About the Role: We are looking for a skilled AI/ML professional to develop, implement, and optimize machine learning models and AI solutions. The role involves data analysis, model training, and integrating AI into real-world applications to solve complex business problems efficiently.Responsibilities:Architect and implement advanced AI solutions leveraging LLMs (and other emerging architectures), embeddings, and agentic frameworks (e.g., OpenAI Agent SDK, AutoGPT, LangChain, CrewAI).Develop and refine Agentic AI systems focusing on planning, memory, tool utilization, and dynamic task critic execution.Engineer and optimize prompt engineering pipelines to achieve superior accuracy and low latency across diverse applications.Fine-tune and deploy specialized LLMs and AI copilots to transform engineering and business operations.Collaborate with cross-functional teams to deliver production-grade solutions that create tangible value.Stay ahead of the curve by integrating emerging GenAI research and state-of-the-art capabilities into practical, real-world systems.Lead projects and mentor junior engineers, contributing to a culture of innovation and growth.Qualifications:Experience: 5+ years of hands-on ML/AI/Deep Learning experience, with a strong portfolio of real-world application development.Technical Proficiency: Advanced Python skills and extensive experience with leading AI tools and libraries (OpenAI, Hugging Face, LangChain, PyTorch, TensorFlow).Core Knowledge: Deep understanding of Large Language Models (LLMs), embeddings, Retrieval Augmented Generation (RAG), and vector databases (e.g., FAISS, Weaviate).Prompt Engineering Mastery: Proven expertise in designing and implementing effective, reusable prompts for complex reasoning, classification, generation, and tool integration tasks across a wide variety of models including open-source solutions.Agentic AI Acumen: Prior experience with autonomous AI agents or multi-agent orchestration is a significant advantage.Mindset: A startup-ready attitude - agile, intellectually curious, and hands-on, thriving in fast-paced, iterative environments.Work Hours and Benefits:Mon – FriPaid time off and holidaysFlexible working hoursOpportunity to work in a dynamic and collaborative environmentProfessional development and training opportunitiesHealth Insurance

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