Senior Agentic AI Engineer

About the job

About the Role We are building a new class of clinical-grade AI agents powered by a foundational model that unifies 3D volumetric medical data and textual reasoning. These agents will assist with radiology workflows, treatment planning, case summarization, longitudinal patient analysis, and human-in-the-loop clinical decision support. In this role, you will design the agent layer that transforms ...  a powerful multimodal foundation model into a safe, reliable, adaptive medical assistant capable of analyzing 3D scans, retrieving past cases, explaining findings, and coordinating multi-step reasoning chains. This position is ideal for researchers from multimodal/VLM/CLIP ecosystems who want to move up the stack into autonomous medical reasoning, multimodal alignment, and real-world clinical impact. What You Will Work On • Architect LLM-driven medical agents capable of: • * Reading & interpreting 3D medical volumes (MRI, CT, PET). • Answering radiology questions, generating report drafts, and performing differential reasoning. • Retrieving similar prior cases using contrastive embeddings. • Synthesizing multi-instance evidence across scans, labs, and notes. • Executing multi-step "clinical workflows"—image analysis summary recommendation. • Integrate clinical agents with the 3D foundation model's representations, enabling structured medical reasoning and contextual memory across longitudinal data. • Develop evaluation frameworks for trustworthiness, interpretability, calibration, and clinical safety. • Collaborate with clinicians and scientists to co-design tasks, datasets, and validation protocols. • Benchmark models against open and proprietary datasets: MIMIC, CheXpert, MosMed, LiTS, BraTS, and India-specific clinical corpora. • Publish findings at top-tier venues (MICCAI, NeurIPS, AAAI, EMNLP). • Work with regulatory and product teams to translate research into medically viable systems. Why This Role Appeals to CLIP / VLM / Chitrarth / Patram Authors • A rare opportunity to work at the intersection of agentic LLMs, multimodal 3D vision, and clinical intelligence. • Ability to bring contrastive learning, cross-lingual modeling, multimodal alignment, and document understanding into the medical domain. • Greenfield space: medical agent design is still unexplored compared to 2D VLMs. • Freedom to publish, open source, and propose new clinical reasoning benchmarks. • Attractive to researchers who want impact beyond academic settings—directly improving physician workflows and patient outcomes. • A chance to create India's first medical foundation-model agent system, setting global standards. What We're Looking For • Experience developing LLM-based agents, tool-using models, chain-of-thought systems, or orchestrated pipelines. • Strong background in multimodal learning, vision–language transformers, contrastive models, or clinical NLP. • Familiarity with medical imaging, radiology workflows, DICOM pipelines, or 3D data representations. • Expertise in PyTorch/JAX and large-scale training and inference. • Ability to design safe, interpretable, and auditable reasoning systems. • Strong publication record in multimodal, medical AI, agentic systems, or LLMs. • Comfort collaborating with clinicians and biomedical researchers. Nice to Have • Experience with agent frameworks (LangChain, LLaMA Index, Haystack, custom pipelines). • Background in clinical ontologies, SNOMED, RadLex, or UMLS. • Contributions to medical AI challenges (BraTS, RSNA, MedVQA, MedIC). • Prior work in multilingual or code-mixed medical text. • Proven ability to take research concepts into production-grade systems.