Job Description

Location: Global (Remote / Hybrid)? Type: Full-Time? Function: Research & Applied AI | Client-Facing? Industries: Retail, Media, Gaming, BFSI, Healthcare & Life Sciences? ? About the Role ? Our client is? seeking a futuristic yet hands-on AI leader who can bridge deep scientific research with real-world impact.? As a Principal AI Scientist , you will drive innovation in Agentic AI systems ?designing, prototyping, and deploying autonomous, reasoning-driven AI architectures that transform how enterprises operate, decide, and engage.? This is a client-facing leadership role that blends scientific depth, architectural vision, and delivery excellence. You will shape the AI strategy, define the architecture, and lead end-to-end execution of cognitive systems that go beyond prediction to decision and action .? ? What You?ll Do ? Architect and operationalize Agentic AI systems that combine reasoning, autonomy, and generative intelligence across Retail, BFSI, Media, Gaming, and Healthcare.? Partner with client executives to define AI roadmaps, frameworks, and architectures that deliver measurable business value.? Prototype, train, and fine-tune large and small language models (LLMs/SLMs) using state-of-the-art frameworks (PyTorch, JAX, Hugging Face, LangGraph, LangChain, RAG).? Lead multi-agent and multi-modal research ?transforming ideas like memory graphs, long-horizon reasoning, and tool-augmented cognition into scalable AI systems.? Collaborate with engineering teams to ensure high-performance model training and deployment on Neo Cloud environments (CoreWeave, RunPod, Lambda, Modal, Together.ai, Vast.ai).? Partner with MLOps and AIOps teams to optimize distributed training, inference pipelines, and GPU utilization across these emerging compute fabrics.? Serve as a thought leader ?conduct client workshops, publish research insights, and represent the company in the broader AI community.? Mentor AI scientists and engineers, cultivating a culture of curiosity, responsibility, and continuous learning.? ? Who You Are ? A scientist?builder hybrid : curious, inventive, and eager to push the limits of what?s possible in intelligent systems.? Comfortable operating across research, engineering, and client advisory ?simplifying the complex and driving value from innovation.? Energized by the convergence of agentic AI, reasoning systems, and large-scale model infrastructure .? ? What You Bring ? Core Qualifications ? PhD or Master?s in Computer Science, AI/ML, Computational Statistics, or related field.? 8+ years in applied AI, ML, or data science, including hands-on deployment of advanced AI systems.? Expertise in foundation models, multi-agent frameworks, and reasoning-based AI architectures .? Deep proficiency in Python , PyTorch , JAX , and LLM orchestration frameworks (LangGraph, LangChain, Hugging Face, RAG).? Hands-on experience with Neo Clouds (CoreWeave, RunPod, Lambda, Modal, Vast.ai, or similar) for distributed training, fine-tuning, and inference optimization.? Familiarity with containerized and GPU-accelerated AI environments (Kubernetes, Ray, Triton Inference Server, DeepSpeed, FSDP/ZeRO).? Strong understanding of MLOps , scaling pipelines , and performance optimization in production.? Prior experience in client-facing roles or consulting environments , translating research to enterprise solutions.? Solid theoretical grounding in reinforcement learning, planning, and cognitive architectures .? Preferred ? Experience designing multi-agent orchestration systems or SLM/LAM architectures for domain-specific automation.? Familiarity with knowledge graphs, contextual memory, and reasoning layers in agentic systems.? Track record of open-source contributions or published research in applied AI.? Proven success in taking AI research prototypes into scalable production systems .? ? Why Join Us ? Shape the next generation of Agentic AI ecosystems powering global industries.? Work on frontier AI infrastructure with access to cutting-edge Neo Cloud platforms.? Collaborate with visionary teams in a zero-legacy, high-autonomy, AI-native environment .? Build cognitive systems that redefine how enterprises think, decide, and act.