Senior Software Engineer - AI

Truveta is the world’s first health provider led data platform with a vision of Saving Lives with Data. Our mission is to enable researchers to find cures faster, empower every clinician to be an expert, and help families make the most informed decisions about their care. Achieving Truveta’ s ambitious vision requires an incredible team of talented and inspired people with a special combination of health, software and big data experience who share our  company values .   This position is based out of our India Development Center in Hyderabad.    Who we are looking for   Join Truveta’s Intelligence Platform and Applications (IPA) team to build the next wave of healthcare AI — developing adaptive agentic systems and fine-tuned foundation models that continuously learn, reason, and accelerate real-world impact. Guided by Truveta’s mission of Saving Lives with Data, you’ll help transform how health data becomes intelligence, powering breakthroughs that enable researchers, clinicians and operational managers to make data-driven, proactive, and impactful decisions. We firmly believe that patients, doctors, and medical researchers deserve to benefit from the artificial intelligence revolution that is transforming productivity, creativity, and communication. You’ll help shape the AI capabilities that make healthcare more intelligent, efficient, and equitable — driving real-world impact across research, care delivery, and patient outcomes. If you’re seeking a sense of purpose and are motivated to advance how AI supports learning, decision-making, and discovery in healthcare, you’ll find this an inspiring place to grow.    We are seeking AI Engineers who thrive at the intersection of agentic and applied AI, machine learning, and large-scale engineering. You’ll blend ML craftsmanship with platform engineering excellence to create scalable, self-improving AI agents and models that learn from vast, diverse healthcare data and deliver meaningful insights through automation and reasoning.  As part of the IPA team, you’ll use your expertise in applied AI, model optimization, and agentic intelligence to create systems that think, adapt, and improve R&D, business strategy, operations and care delivery across the healthcare ecosystem. You’ll work in an ambitious, fast-paced and collaborative environment where every contribution helps make healthcare more connected, intelligent, and impactful.   Required skills   Agentic AI   Design and reason with agentic AI frameworks — experienced in building multi-agent workflows using frameworks such as LangGraph, AutoGen, or CrewAI, integrating reasoning, reflection, planning, tool use and memory to create intelligent, goal-driven systems. Have a deep understanding of capabilities of multi-modal models in agentic systems.   Understand evaluation deeply — fluent in ML validation and measurement (Precision, Recall, Specificity, NPV, etc.), and experienced designing reward functions, evaluators, or grader models for reinforcement fine-tuning and continuous improvement. Good understanding of LLM as judges for qualitative and semantic evaluations.   Fluency in embeddings and vector stores — experienced in building or integrating retrieval-augmented generation (RAG) pipelines, managing vector databases (e.g., FAISS, Pinecone, Chroma, Azure AI Search, or similar), and leveraging semantic search or context injection to enhance reasoning.    Adapt and learn continuously — staying ahead of evolving AI architectures, agentic frameworks, and emerging paradigms in reasoning and retrieval. You have curiosity, humility, and a bias for iteration.    Machine Learning and LLMs   A solid understanding of classical ML, and LLM fundamentals — knowledgeable in transformer architectures, attention mechanisms, and tokenization principles. You understand how embeddings, context windows, and model scaling laws influence quality, cost, and performance.    Excellence in model fine-tuning — with hands-on expertise fine-tuning large language models (LLMs) or multimodal models using supervised, reinforcement, or instruction-tuning techniques (e.g., LoRA, PEFT, TRL). Skilled at optimizing model efficiency, interpretability, and inference performance.    Thought leadership     As a senior member of the development team, you must provide thought leadership to the team in the following areas:   Collaboration across boundaries — partnering with platform, application, and product engineers to transform concepts into scalable, reliable AI solutions. You communicate clearly, share knowledge openly, and thrive in cross-functional teams.    Solid engineering — grounded in strong software design principles, modular architecture, and code quality. You can translate experimental ideas into robust, maintainable systems that integrate seamlessly within large-scale AI platforms.    Demonstrating ownership