Job Title: AI/ML Engineer – Agentic AI DEVELOPER Location: Remote Level: 8+ years (including 3+ years in leading AI/ML projects) Job Summary: We are seeking a hands-on AI/ML Engineer with deep technical expertise in building and deploying intelligent agentic systems. As the Tech Lead, you will drive the development of AI agents capable of autonomous decision-making and multi-step task execution using LLMs, reinforcement learning, and orchestration frameworks. This is a highly impactful role combining leadership, innovation, and advanced engineering. Key Responsibilities: • Architect, design, and implement agentic AI systems leveraging LLMs, RLHF, and task planning frameworks • Lead development of autonomous, multi-agent frameworks for enterprise and consumer applications • Develop scalable ML pipelines and serve as the SME for intelligent agent design • Fine-tune and prompt large language models (LLMs) such as GPT, Claude, or Mistral for domain-specific use cases • Integrate external APIs and tools into AI agent workflows for tool-use, memory, and reasoning • Collaborate with product, research, and engineering teams to prototype and deploy cutting-edge solutions • Mentor junior engineers and contribute to technical strategy and roadmap • Stay ahead of research trends in autonomous agents, LLM chaining, and AI orchestration (e.g., LangChain, CrewAI) Required Qualifications: • Bachelor's or Master’s in Computer Science, AI/ML, or related field (PhD is a plus) • 6–10 years of experience in machine learning, with 2–3 years focused on LLMs or agentic architectures • Strong proficiency in Python and ML frameworks like PyTorch or TensorFlow • Experience working with LLMs (e.g., OpenAI, Anthropic, Meta, Cohere APIs or open-source models) • Familiarity with LangChain, Semantic Kernel, CrewAI, AutoGPT, or similar frameworks • Deep understanding of transformers, NLP, prompt engineering, and multi-agent design patterns • Experience in deploying AI/ML models to production (Kubernetes, Docker, CI/CD, cloud platforms) Preferred Skills: • Knowledge of knowledge graphs, vector stores (e.g., Pinecone, FAISS), and RAG pipelines • Experience with orchestration platforms and workflow agents (e.g., Flowise, DSPy, Haystack) • Exposure to reinforcement learning, curriculum learning, or policy-based agent models • Prior experience in building AI copilots, chatbots, or intelligent assistants