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# Principal Data Scientist z GenAI - Full remote (F/M)

- **Company:** Astek Corporation
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $332,800
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Artificial Intelligence, Amazon Web Services, Automation of Tests, Microsoft Azure, Cloud Computing, High-Level Architecture, Information Retrieval, Python (Programming Language), Machine Learning, Computational Statistics, Retrieval-Augmented Generation, Large Language Models, Grafana, Multi-Agent Systems, Hallucination Detection, Llamaindex, AgentCore, Agentic-AI, Event Driven Architecture, Information Technology, Low Latency, Deployment Automation, Performance Monitor, Machine Learning Operations, Evaluation of Large Language Models, Natural Language Generation
- **Published:** November 5, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pwtuh8tscm

## About the Role

* Have 8+ years of hands-on experience in Data Science, Machine Learning, or AI Engineering, with strong expertise in advanced statistics and probability.
 * Can confidently discuss Bayesian inference, uncertainty quantification, model calibration, causal reasoning, and evaluation methodologies with PhD-level experts.
 * Have designed and deployed production-grade GenAI solutions, including LLMs, RAG pipelines, and agentic AI systems.
 * Have hands-on experience architecting complex agentic workflows, including multi-agent orchestration, tool integration, and multi-model architectures.
 * Know how to evaluate, monitor, and optimize AI systems for quality, reliability, scalability, latency, and cost.
 * Have strong Python skills and practical experience with MLOps, cloud platforms (AWS, Azure, or GCP), and production AI deployments.
 * Can lead multiple AI engineering teams, make complex architectural decisions, and remain actively involved in technical problem-solving.
 * Understand enterprise AI security, data confidentiality, and responsible AI governance, ideally within a regulated industry such as pharmaceuticals or healthcare.
 * Can bridge advanced mathematical thinking, practical AI engineering, and business needs.

Nice to have:

 * PhD or advanced degree in Mathematics, Statistics, Computer Science, Machine Learning, or a related quantitative field.
 * Hands-on experience with agentic AI frameworks such as LangGraph, LangChain, or LlamaIndex.
 * Experience with AWS services, particularly Bedrock, AgentCore, SageMaker, and Lambda.
 * Experience designing and scaling multi-agent AI systems in enterprise environments.
 * Knowledge of advanced RAG techniques, including hybrid search, semantic retrieval, reranking, and retrieval evaluation.
 * Experience with LLM evaluation frameworks, observability tools, and automated quality testing.
 * Familiarity with multi-model routing, LLM cost optimization, and high-concurrency AI architectures.
 * Experience with event-driven architectures, CI/CD pipelines, and Infrastructure as Code.
 * Previous experience in pharmaceutical, healthcare, or other highly regulated industries.
 * Familiarity with enterprise AI governance, data privacy, and regulatory compliance requirements.
 * Experience leading geographically distributed AI/ML engineering teams.

## Description

We are currently looking for a candidate for the position of Principal Data Scientist z GenAI for our client from the Life Science industry., * Leading the technical architecture, design, and development of production-grade GenAI, RAG, and Agentic AI solutions.

 * Providing hands-on technical leadership across two AI engineering teams, guiding architectural decisions, solving complex technical challenges, and ensuring engineering best practices.
 * Designing and optimizing agentic AI workflows, including multi-agent orchestration, tool integration, and multi-model architectures.
 * Developing and improving RAG pipelines to ensure high retrieval accuracy, reliability, scalability, and cost efficiency.
 * Applying advanced statistical and Machine Learning methodologies to evaluate model performance, uncertainty, calibration, and reliability.
 * Collaborating with senior Data Scientists and quantitative experts to challenge analytical assumptions, validate methodologies, and ensure scientific rigor.
 * Establishing robust GenAI evaluation and observability frameworks, including hallucination detection, automated testing, tracing, and performance monitoring.
 * Overseeing the deployment, monitoring, and continuous improvement of AI models and agents in production environments.
 * Ensuring AI solutions comply with enterprise architecture standards, data confidentiality requirements, security policies, and responsible AI governance.
 * Working closely with AI Engineers, Data Scientists, Architects, and business stakeholders to translate complex business requirements into scalable technical solutions.
 * Mentoring engineers, reviewing technical designs, and driving engineering standards across geographically distributed teams.
 * Identifying opportunities to improve AI system performance, reliability, scalability, and operational efficiency.