Only accepting local Seattle, WA candidates

We are seeking an Applied Scientist / Data Scientist with strong expertise in Generative AI, LLMs, RAG architectures, and AWS Bedrock to build next‑generation AI capabilities for enterprise‑scale use cases. This role focuses primarily on applied AI/LLM system development, while also leveraging traditional data science and machine learning skills to support broader modeling and analytics needs.

This position requires 5 days/week on‑site in Seattle, WA and the ability to interview in person on short notice.

⭐ What You’ll Do (Applied Scientist Focus)

• Design, build, and deploy enterprise-grade LLM applications using modern foundation models.
• Develop RAG pipelines, vector-based retrieval, and contextual knowledge bases.
• Engineer agentic AI workflows, multi-step reasoning chains, and autonomous decision systems.
• Perform prompt engineering, optimization, evaluation, and guardrail construction.
• Identify and mitigate hallucinations, design safety layers, and tune system reliability.
• Build scalable, production-ready GenAI solutions leveraging AWS Bedrock and related services.
• Collaborate with engineering and product teams to bring GenAI prototypes into full production.

🔍 Data Scientist Responsibilities (Secondary but Required)

• Apply traditional ML techniques (classification, regression, clustering, etc.) when GenAI is not the right fit.
• Conduct data exploration, feature engineering, and statistical analysis to support use‑case discovery.
• Build, tune, and validate predictive models using established ML frameworks.
• Analyze system performance, model outputs, and user interaction patterns.
• Translate data insights into actionable recommendations for leadership and clients.
• Support experimentation, A/B testing, and model performance measurement.

These responsibilities ensure a well-rounded individual capable of bridging both emerging GenAI technologies and core data science fundamentals.

✔️ What You Bring

Technical Expertise:

• Strong background in Applied Science, Data Science, Machine Learning, or AI Engineering.
• Hands‑on experience with:
  • LLMs (enterprise-grade)
  • AWS Bedrock
  • RAG architectures
  • Prompt engineering
  • Agentic AI workflows
• Solid grounding in traditional ML (Python, scikit‑learn, data wrangling, evaluation metrics).
• Experience building scalable AI systems and integrating them into real-world workflows.

Communication Skills:

• Ability to explain complex AI concepts clearly to executives, engineers, and non‑technical stakeholders.
• Strong presentation and client‑facing communication skills.

🎯 Why This Role Is Unique

• You’ll work at the intersection of research-level innovation and real enterprise deployment.
• Build solutions that go beyond prototypes into production AI systems that matter.
• High executive visibility and the chance to influence AI strategy.
• Opportunity to work across both GenAI and traditional ML, giving variety and depth to your work.

🧪 Interview Process

• Short introductory conversation
• 60-minute technical interview (LLMs, RAG, GenAI reasoning, and ML fundamentals)
• Client virtual interview, followed by an in‑person meeting for finalists

🌟 If you’re an Applied Scientist with strong Data Science fundamentals and a passion for building real GenAI solutions, this is an opportunity to help shape the next wave of enterprise AI.