AIMl Engineer

Key Responsibilities:

• Architect and implement advanced AI solutions leveraging LLMs (and otheremerging architectures), embeddings, and agentic frameworks (e.g., OpenAI Agent SDK, AutoGPT, LangChain, CrewAI).
• Develop and refine AgenticAI systems focusingon planning, memory,tool utilization, and dynamic task critic execution.
• Engineer and optimize prompt engineering pipelines to achieve superioraccuracy 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 deliverproduction-grade solutions that create tangible value.
• Stay ahead of the curve by integrating emergingGenAI 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

Required Qualifications:

• Experience: 3-8 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

  Role & responsibilities