Agentic and Generative Data Scientist II

We’re hiring a Agentic and Generative Data Scientist II to design and deploy AI systems end-to-end: from data preparation and evaluation to model fine-tuning, inference, and agentic workflows. You’ll partner closely with product and engineering to ship reliable, cost-effective, and scalable LLM-powered solutions on AWS., The essential functions include, but are not limited to the following:

• End-to-end GenAI solutions: Scope problems, choose the right approach(prompt engineering, fine-tuning, agents), implement, evaluate, and deploy.
• Data & SQL: Write efficient SQL for analytics and data preparation; manage schemas and pipelines for model training and inference.
• Model training & fine-tuning: Run supervised fine-tuning (PEFT/LoRA/QLoRA), optimize prompts, and manage experiment tracking and evaluation.
• Agentic systems: Build agent workflows with tool use, memory, and safety/guardrails.
• Inference & deployment: Package services with Docker, optimize latency/cost (batching, caching, quantization), and deploy on AWS (ECS, EKS, SageMaker, Lambda with GPU acceleration).
• MLOps & Observability: Set up CI/CD for models/prompts, maintain offline/online evaluation pipelines, monitoring, and rollback strategies.
• Security & compliance: Implement data governance, PHI/PII protections, and guardrails against prompt injection and unsafe outputs.
• Cross-functional work: Collaborate with product managers and engineers to align GenAI capabilities with product goals; document clearly and communicate trade-offs.
• Production readiness: Lead conversations around scaling, monitoring, and maintaining GenAI systems in real-world environments., Work is typically in a normal office administrative environment involving minimal exposure to physical risks. Position requires little to moderate physical activity. Mostly sedentary work exerting up to 10 pounds of force occasionally or a negligible amount of force to lift, carry, push, pull, or otherwise move objects. Work involves sitting most of the time, but may involve walking or standing for brief periods of time. No significant stooping is usually required.

• Bachelor’s Degree or equivalent experience required; Master’s degree preferred., * 5+ years of Software/ML engineering experience, including 2+ years building and deploying GenAI/LLM systems.
• MS/PHD in Computer Science or equivalent experience.
• Strong SQL and Python skills with solid software engineering fundamentals.
• Experience with agent frameworks (LangGraph, AutoGen, CrewAI) and building tool-driven agents.
• Hands-on with deep learning (PyTorch or TensorFlow) and LLM fine-tuning(SFT/PEFT like LoRA/QLoRA).
• Production experience with Docker and deploying on AWS (ECS, EKS,SageMaker, Lambda, or GPU services).
• Experience creating Data and Model pipelines for model training anddeployment at scale.
• Familiarity with prompt engineering, evaluation frameworks (LLM-as-judge,metrics), and offline test harnesses.

• Understanding of security & compliance for sensitive data (e.g., PHI/PII) and safe deployment of AI systems.

• Excellent problem-solving, communication, and documentation skills.
• Inference optimization: quantization (bitsandbytes, GPTQ/AWQ), batching, caching, or vLLM.
• Healthcare experience: familiarity with HIPAA, medical data handling, or working in health tech.
• Experiment tracking (MLflow, W&B), CI/CD for ML, and monitoring (Prometheus, Grafana).
• Familiarity with major LLM APIs and OSS models (OpenAI, Anthropic, Llama, Mistral).

Other: Tech Stack

• Languages: Python, SQL
• DL/LLM: PyTorch, Tensorflow, Hugging Face, PEFT/TRL, vLLM
• Data: Snowflake, Postgres
• Cloud: AWS (ECS, EKS, SageMaker, Lambda)
• MLOps: Docker, CI/CD, MLflow or W&B

Xsolis is an AI-driven technology company with a human-centered approach, fostering collaboration between healthcare providers and payers through real-time transparency, objective data for increased accuracy and alignment of medical necessity decisions, and more efficient outcomes. Dragonfly®, its AI-driven proprietary platform, is the first and only solution to use real-time predictive analytics to continuously assign an objective medical necessity score and assess the anticipated level of care for every patient, enabling more efficiency across the healthcare system. Xsolis is headquartered in Franklin, Tennessee. Our Values:

• Team First
• Client Passionate
• Always Curious
• Deliver Excellence

Xsolis has been ranked on the Inc. 5000 and Deloitte Technology Fast 500 lists in both 2022 and 2023 as a fastest-growing private company, and was named 2022 Best in Business among private companies by the Nashville Business Journal. Xsolis executives have been featured in Becker’s Hospital Review, Becker’s Payer Issues, Chief Healthcare Executive, CIO Review, Managed Healthcare Executive, Medical Economics, HIT Consultant, Healthcare IT Today, among other leading publications. For more information, visit www.xsolis.com. Where We’ll Go Together

Our company will become the new standard for utilization management. You’ll be a core part of realizing that goal and a valued contributor to the culture and climate we wish to create. Our wins are your wins, and we’re dedicated to making you feel your work matters (it truly does). If any of this speaks to you, let’s get in touch.