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

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.

• 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.

Offered salary

Salary: from 160 to 200 PLN net/day, depending on experience and competences., * Technical training, certifications, and skills development

• Competence Center mentoring - being a member of the Competence Center community from day one is an opportunity to develop your skills, participate in various conferences, and share knowledge and experience with people who face the same challenges every day
• Clear career path
• Employee benefits package (Multisport, private healthcare, life insurance)
• Friendly working atmosphere, team-building events, and team-building meetings

Referral system

It’s not about you? Recommend us your friend and get a bonus up to 7,000 PLN Link: https://astek.pl/system-rekomendacji