3 senior ai software engineer jobs found

Overview Good things are happening at Berkshire Hathaway GUARD Insurance Companies—an A+ (Superior) rated, nationwide Property & Casualty insurer backed by Berkshire Hathaway. With supportive leadership, collaborative teams, and opportunities to grow, GUARD is a place where people build meaningful, long‑term careers. Good Things You Can Count On. •  Hybrid schedule: 2 days remote / 3 in‑office •  Predictable hours (no nights, weekends, or holidays) •  Competitive pay + generous PTO •  Medical, dental & vision starting day one •  401(k), tuition reimbursement & longevity bonuses   Responsibilities We are growing our engineering organization and seeking Full Stack Developers across all experience levels who are excited about modern software development and AI-enabled engineering practices . This is an opportunity to work in an environment where cloud-first architecture, automation, and...

As a Tech Lead, you’ll serve as the hands-on technical leader for a team within Guardian’s Digital & Technology organization. You’ll guide engineers in building secure, scalable, and high-performing solutions, while ensuring engineering practices align to Guardian’s architectural and delivery standards. Working closely with the Product D&T Leader and Product Owner, you’ll translate business outcomes into technical execution and foster a culture of engineering excellence You Are A self-starter, continuous learner and hands-on technical engineer who can translate vision from the Platform / Product D&T leader into development by partnering across the engineers, product managers, business partners and executive stakeholders.   You Will Lead and mentor a team of software engineers, fostering a collaborative and high-performing environment. Architect, design, and develop robust, scalable, and secure software applications using modern engineering practices....

Primary Details Time Type: Full time Worker Type: Employee AI Engineer – Role Overview Specialises in designing and deploying GenAI solutions by crafting effective, domain-specific prompts and ensuring scalable, production-ready integration through MLOps practices. Key Responsibilities/Qualifications: • Prompt Engineering: Create and optimise prompts to drive accurate and relevant LLM outputs tailored to specific business needs. • Business Domain Acumen: Collaborate with stakeholders to understand industry-specific terminology, processes, and challenges, enabling more effective AI solutions. • MLOps Integration: Build, deploy, and manage GenAI pipelines using platforms such as MLflow or Azure ML, ensuring reliability, scalability, and maintainability. • Responsible AI: Apply principles of fairness, transparency, and security, including bias mitigation and model explainability. Responsibilities: Analyse business requirements, design and implement solutions....