Role: Applied AI Scientist.
Experience: 7+ years
Location: Remote
Required Skills: ML, RAG, LLMs, Gen AI, Agentic AI, Applied Generative AI
Key Responsibilitie
- sAI Solution Development: Combine classical ML and cutting-edge Gen AI/agentic methods to solve key business challenges and drive operational efficiency
- .Proof-of-Concept & Experimentation: Plan and execute structured PoCs for Generative and Agentic AI systems—covering large-scale prompt optimization, fine-tuning, and model selection
- .Evaluation & Benchmarking: Design robust evaluation frameworks, define quantitative quality metrics, and construct benchmarks to test real-world AI performance
- .Quality & Safety Assurance: Establish groundedness, safety, and hallucination metrics to ensure trustworthy AI behavior
- .Model Analysis: Analyze foundation model behavior in dev/prod environments to identify failure modes, bias, and performance limits
- .Cross-Functional Collaboration: Translate complex AI concepts into clear, accessible insights for operational stakeholders and non-technical business partners
- .Agile Culture: Contribute to the AI Enablement operating model, adopting agile methodologies and building reusable AI best practices
.
What We're Looking Fo
r:Education & Experien
- ceRequired: Bachelor's degree in a STEM field with experience applying data science in a commercial settin
- g.Preferred: Master's degree or higher in a STEM fiel
d.Technical Skil
- lsStrong foundation in statistical modeling and classical Machine Learnin
- g.Hands-on experience with GenAI methods: prompt engineering, RAG, fine-tuning strategies, and LLM output assessmen
- t.Experience building and operationalizing Agentic AI solution
- s.Proven track record designing evaluation frameworks, benchmark construction, A/B testing, and quality metric
- s.Excellent data visualization and technical communication skill
- s.(Bonus) Familiarity with the Insurance domain or experience in a regulated industr
y.
