Senior AI Engineer

MUST- Sr level Engineer with AI exp
How do use AI to solve a business problem?
- Familiar with Claude code or Cursor
- MUSt have Java development experience
- Engaging daily with business partners
- MUST- People person- Soft skills, communication and ability to gel well, ability to connect with people, bring enthusiasm
They will be lots of questions in the interview about how approach, how engage the customer? Customer engagement is critical, and soft skills are key.
MUST- Prompt Engineering
- Work with underwriters to get reqs and use Claude code to build solutions
MUST be very personable, polished and speak well, ability to build relationships and work with others in a small group setting
- They are very cross functional and need to adapt to the business
- They are building prototypes now and goal is to go to production within another team
- Help build prototypes, understand the model Gemini gives them
- Using embeddings, Prompt engineering within the PODS

Experience & Qualifications

Overall Career: 10+ years of professional experience in software engineering, systems design, or technical prototyping.

AI Prototyping & Frameworks: 2+ years of hands-on experience building AI-augmented tools, Retrieval-Augmented Generation (RAG) pipelines, or prompt-based systems.

AI-Assisted Tooling Literacy: Demonstrated fluency using advanced LLM-based engineering ecosystems (such as Claude Code (preferred) or Cursor or CoPilot) to drastically accelerate software delivery cycles.

Domain Expertise: Prior background in the Insurance or Financial Services sector is highly preferred; direct exposure to underwriting processes is a massive advantage.

Required Skills

AI-Native Engineering: Expert capability in prompt engineering, context window management, and designing robust RAG (Retrieval-Augmented Generation) architectures.

Consultative Communication: Exceptional soft skills with a proven track record of collaborating directly with non-technical business stakeholders daily to uncover technical needs.

Agile Prototyping Mindset: A strong bias for action and velocity. Ability to build functional, adaptable prototypes and portals within a 3 6 month lifecycle without getting bogged down by tech-stack rigidity.

Cross-Functional Collaboration: A true team player comfortable operating within active Agile pods alongside Tech Leads, Architects, and business partners.

Team Leadership & Mentorship: Proven ability to provide technical guidance, mentorship, and oversight to fellow pod members. Must possess the leadership capacity to foster collaboration, elevate the team's technical execution, and ensure all deliverables meet the highest standards of quality and efficiency.

Technical Versatility: While Python is highly valued for modular AI development, we prioritize a tech-agnostic ability to choose and utilize the right tool or framework to bring an AI concept to life quickly.