Software Development Engineer II, Generative AI
Key Skills for This Role
Full Job Posting
Qualifications
- 3+ years of industry experience in software engineering, data science, or machine learning.
- 1+ years of hands-on experience building GenAI/LLM-based features or applications, ideally in a production setting.
- Strong Python skills and experience with modern AI/ML and GenAI frameworks and tooling.
- Working understanding of LLMs, embeddings, RAG, prompt engineering, context Engineering, and GenAI architecture patterns.
- Experience with cloud-native architectures and deploying scalable applications to production.
- Understanding of GenAI evaluation, testing, monitoring, and responsible AI practices.
- Ability to work with moderate autonomy, break down ambiguous problems, and communicate technical tradeoffs clearly.
- Genuine curiosity and enthusiasm for learning new technologies, tools, and techniques in a fast-moving field.
- Bachelor's degree in Computer Science, Software Engineering, Machine Learning, Data Science, or a related technical field.
- Additional Qualifications
- knowledge on fine-tuning or adapting LLMs (e.g., SFT, LoRA/PEFT, instruction tuning), including preparing training datasets or evaluating fine-tuned models against baselines is a plus.
- Experience with agentic AI patterns or multi-step LLM workflows is a plus.
- #LI-MB1
- #LI-Hybrid
Responsibilities
- Build features and components for production-grade GenAI products, with a focus on quality, reliability, and performance.
- Implement and iterate on LLM-based solutions, including retrieval-augmented generation (RAG), prompt engineering, context Engineering, Loop Engineering and agentic workflows.
- Write clean, well-tested, maintainable Python code and contribute to the broader codebase and infrastructure.
- Help build evaluation and monitoring pipelines to measure output quality, groundedness, and reliability of GenAI features.
- Work with foundation models and GenAI frameworks/tooling, evaluating tradeoffs between approaches under guidance from senior engineers.
- Collaborate with Product Owners and cross-functional stakeholders to translate requirements into working technical solutions.
- Participate in code reviews, design discussions, and engineering best practices across the GenAI development lifecycle.
- Debug and resolve technical issues across the stack, escalating and collaborating with senior team members on complex problems.
- (SDE II) Take ownership of medium-complexity features end-to-end, mentor SDE I engineers, and contribute to architecture and design decisions for GenAI components.
Preferred Qualifications
- knowledge on fine-tuning or adapting LLMs (e.g., SFT, LoRA/PEFT, instruction tuning), including preparing training datasets or evaluating fine-tuned models against baselines is a plus.
- Experience with agentic AI patterns or multi-step LLM workflows is a plus.
About Verisk Analytics
Global data analytics and technology partner to the insurance industry.
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