Lead AI Engineer

About the Company

We are a forward-thinking technology company dedicated to pushing the boundaries of artificial intelligence. Our mission is to innovate and create solutions that enhance business operations and improve lives. We foster a culture of collaboration, creativity, and continuous learning.

About the Role

The role involves architecting and implementing advanced AI solutions leveraging LLMs and other emerging architectures, focusing on creating impactful systems that drive efficiency and innovation.

Responsibilities

• Architect and implement advanced AI solutions leveraging LLMs (and other emerging architectures), embeddings, and agentic frameworks (e.g., OpenAI Agent SDK, AutoGPT, LangChain, Crew AI).
• Define AI strategy and lead endtoend design, deployment, and scaling of AI systems.
• Mentor AI/ML engineers, enforce best practices, and ensure code and model quality.
• Collaborate with product, data, and engineering teams to align AI solutions with business goals.
• Own AI architecture, MLOps, performance monitoring, and risk/ethics compliance.
• 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 Gene AI research and state-of-the-art capabilities into practical, real-world systems.

Qualifications

• Experience: 8-12 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, We aviate).
• 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.

Required Skills

• Advanced Python skills
• Experience with leading AI tools and libraries
• Deep understanding of LLMs and embeddings
• Expertise in prompt engineering
• Experience with autonomous AI agents

Preferred Skills

• Experience with multi-agent orchestration
• Familiarity with open-source AI solutions