AI Architect

• We are seeking a visionary AI Architect to lead the design and development of our next-generationAgentic AI Studio a platform focused on intelligent, autonomous GenAI agents capable ofreasoning, decision-making, and multi-step task execution across enterprise workflows
• This is a hands-on architecture leadership role, where you will work at the intersection of LLMs,cognitive agents, tool use, and multi-agent orchestration, collaborating with product, research, andengineering teams to build scalable systems that go beyond traditional prompt engineering

Roles & Responsibilities

• 10+ years (including 4+ years in GenAI and autonomous agent systems) Proven experience designing LLM-powered agents with long-term memory, tool-use, planning, and goal-directed reasoning
• Strong expertise in agentic frameworks like AutoGen, CrewAI, LangGraph, ReAct, CAMEL and BabyAGI
• Experience in multi-agent orchestration, task delegation, and collaborative planning between agents Deep knowledge of RAG pipelines, vector search (eg, FAISS, Weaviate, Pinecone), and embedding strategies
• Strong proficiency in LLM fine-tuning (SFT, LoRA, PEFT) and working with Hugging Face, OpenAI, Claude, etc
• Skilled in building and integrating tool-augmented agents using APIs, retrieval plugins, code execution, etc
• Familiarity with LangChain, LangGraph, LangFlow, and other orchestration librarie Deep hands-on with Python, FastAPI, cloud services (AWS, GCP, Azure), and infrastructure automation (Terraform, CI/CD) Exposure to cognitive architectures (SOAR, ACT-R, OpenCog, Leabra)
• Understanding of agent simulation environments, reinforcement learning, or curriculum-based training
• Experience integrating agents into LMS, enterprise SaaS, or knowledge work platforms
• Knowledge of event-driven, goal-based task scheduling and real-time coordination systems Familiarity with Langfuse,
• PromptLayer, Traceloop, or custom observability pipelines for agents
• Prior work on memory management, context windows, and scalable vector DB partitioning
• Defining the overall architecture of Agentic AI Studio, from agent lifecycle to orchestration and observability
• Designing and deploying scalable agent runtimes, leveraging cloud-native tools and GPU inference platforms
• Leading development of multi-agent coordination protocols, goal resolution, and autonomous workflows
• Driving experimentation with new agentic behaviors, planner-tool integration, and long-term memory systems
• Collaborating with data, infra, and product teams to integrate agentic intelligence into real- world business tasks
• Establishing architectural standards for observability, explainability, and safety of AI agents
• Mentoring engineers and evangelizing agent-based AI thinking across the organization