Senior Applied AI Scientist

Cherry Bekaert Recruiting & Staffing Services; United States; On-site; USD 170,000 - 210,000; Full time

Job summary

Cherry Bekaert Recruiting & Staffing Services is seeking a Senior Applied AI Scientist to design, build, and deploy production-grade AI/ML solutions at scale in the healthcare and life sciences sector.

The role focuses on generative and agentic AI systems, retrieval-augmented generation, and integration of LLMs with orchestration, memory, and multi-step workflows. Strong Python and ML fundamentals are essential.

Qualifications

• 5+ years of hands-on experience developing machine learning, data science, or applied AI solutions.
• Demonstrated experience building and deploying AI or ML systems in production environments.
• Advanced Python development skills and experience building reliable software.
• Strong foundation in traditional ML including feature engineering, training, validation, experimentation, and evaluation.
• Hands-on experience developing generative AI applications using LLMs, retrieval-augmented generation, embeddings, vector search.
• Experience building agentic or orchestrated AI workflows using LangChain, LangGraph, or comparable technologies.
• Experience developing production APIs, microservices, or model-serving apps with FastAPI.
• Understanding of AI system design, scalability, testing, monitoring, security, latency, and cost.

Responsibilities

• Design, develop, and deploy production-grade AI and ML solutions for enterprise and client-facing apps.
• Architect generative and agentic AI systems with LLMs, retrieval, tool calling, orchestration, memory, and multi-step workflows.
• Build RAG pipelines integrating structured/unstructured data, embeddings, vector search, and domain knowledge.
• Develop and maintain scalable Python apps, APIs, microservices, and model-serving components.
• Move solutions from experiments to production with monitoring and continuous improvement.
• Collaborate with engineering, product, data, and business teams to translate requirements into scalable solutions.
• Mentor junior team members and contribute to code quality and documentation.

Skills

Python programming

Traditional ML foundations

Cross-functional collaboration

Tools

LangChain

LangGraph

FastAPI

PyTorch

TensorFlow

Job description

Senior Applied AI Scientist, Generative & Agentic AI

Base Salary: Approximately $170,000–$210,000 + 15% Bonus

Cherry Bekaert Recruiting & Staffing Services is partnering with a rapidly growing global data and analytics organization investing heavily in AI and machine learning across its healthcare and life sciences platform.

The team is seeking a Senior Applied AI Scientist to design, build, and deploy production-grade AI/ML solutions. This is a highly hands-on role for someone who combines strong traditional machine learning fundamentals with experience building generative and agentic AI systems from prototype through production.

Key Areas of Focus

• Generative AI and large language models
• Agentic and multi-step AI workflows
• Retrieval-augmented generation
• LLM and agent orchestration
• NLP and deep learning
• Traditional machine learning and predictive modeling
• Knowledge graphs and semantic retrieval
• AI evaluation, testing, and observability
• Production AI applications and services

Responsibilities

• Design, develop, and deploy production-grade AI and machine learning solutions for large-scale enterprise and client-facing applications.
• Architect generative and agentic AI systems incorporating LLMs, retrieval, tool calling, orchestration, memory, and multi-step workflows.
• Build RAG pipelines that integrate structured and unstructured data, embeddings, vector search, and domain-specific knowledge.
• Develop and maintain scalable Python applications, APIs, microservices, and model-serving components.
• Apply traditional machine learning, statistical modeling, NLP, and deep learning techniques to complex business problems.
• Establish evaluation frameworks for AI systems, including retrieval quality, model accuracy, hallucination risk, agent behavior, reliability, latency, and cost.
• Move solutions from experimentation and proof of concept through production deployment, monitoring, and continuous improvement.
• Contribute to system architecture, technology selection, model optimization, and AI engineering standards.
• Partner with engineering, product, data, and business stakeholders to translate ambiguous requirements into practical and scalable solutions.
• Mentor junior team members and contribute to code quality, technical documentation, and development best practices.
• Evaluate emerging AI models, frameworks, and techniques based on their practical value and production readiness.

Required Qualifications

• 5+ years of hands-on experience developing machine learning, data science, or applied AI solutions.
• Demonstrated experience building and deploying AI or machine learning systems in production environments.
• Advanced Python development skills and experience building reliable, maintainable software.
• Strong foundation in traditional machine learning, including model development, feature engineering, training, validation, experimentation, and performance evaluation.
• Hands-on experience developing generative AI applications using LLMs, retrieval-augmented generation, embeddings, vector search, or related techniques.
• Experience building agentic or orchestrated AI workflows using frameworks such as LangChain, LangGraph, or comparable technologies.
• Experience developing production APIs, microservices, or model-serving applications using tools such as FastAPI.
• Understanding of AI system design, including scalability, testing, monitoring, reliability, security, latency, and cost considerations.
• Experience using modern ML and AI libraries such as pandas, scikit-learn, PyTorch, TensorFlow, Hugging Face, or comparable frameworks.
• Strong analytical, problem-solving, communication, and cross-functional collaboration skills.