AI Observability Engineer

Be part of something groundbreaking

At AIG, we are making long-term investments in a brand-new,
innovative Generative AI team
, designed to explore new possibilities for how artificial intelligence can be applied in insurance and beyond, and we need your help.

AIG is a leading global insurance organization providing a wide range of property casualty insurance and other financial services. We provide world‑class products and expertise to businesses and individuals in approximately 190 countries and jurisdictions.

At AIG, we’re reshaping how the world manages risk, and we’re inviting you to be a key part of that transformation. As an AI Observability Engineer, you will have the opportunity to make a meaningful impact, leveraging and further developing your skills to guide groundbreaking AI initiatives. If you’re looking for a place to grow your career and where your contributions will shape the future, AIG is where you belong.

The AI Observability Engineer plays a critical role in interaction with our AI product teams to ensure the AI solutions are aligned with the enterprise Responsible AI principles and standards. Additionally, the AI Observability Analyst supports the design and execution of the overall AI Governance program as well as the communication and awareness initiatives associated with Responsible AI principles and methods through the following activities:

• Model Performance Monitoring:
  Tracking ML, LLM, Agentic AI key performance indicators (KPIs) like context relevance, accuracy, precision, recall, and F1 scores to ensure model effectiveness
• Data Quality and Bias Detection:
  Monitoring data inputs for anomalies, bias, and drift, which can impact the fairness and accuracy of AI systems
• Utilize observability tools to produce structured, trustworthy insights from detailed data sets on AI system activities.
• Manage on‑going operations of our AI model management platform and pipelines including evolving our KPIs and model observability capabilities
• Review AI solutions across the business to ensure alignment with AIG’s Organizational Policies, AI Governance Framework and Responsible AI principles
• Provide support to AI product teams, conduct independent reviews, respond to ad‑hoc queries, and participate in workshops
• Collaborate with legal, compliance, security, and other teams to coordinate the review of Responsible AI issues, ensuring a cohesive approach across the organization
• Create executive‑level reports on Responsible AI and provide strategic recommendations to senior leadership
• Create and update RAI training content for technical and non‑technical audiences at all levels of seniority
• Contribute to the development and improvement of RAI assets: methods, technical tutorials, tools
• Monitor and remain up to date on emerging global AI regulatory frameworks, standards and policies by participating in workshops, reading publications, networking with the goal of helping to translate into RAI framework updates

• Minimum 3 years’ experience and a Bachelor’s degree is required.
• Machine Learning, Large Language Models knowledge of various models, algorithms, and evaluation metrics is crucial for effective monitoring.
• Data pipelines and analysis skills with the ability to handle, clean, and transform data for monitoring and analysis.
• Excited about the problem of scaling human oversight of AI systems and familiar with LLMs development.
• Comfort with ambiguity and curiosity as our team is scaling with strong ownership.
• You bring experience and passion in Responsible AI or AI ethics, with an understanding of AI technologies and frameworks such as Generative AI.
• You have a strong ability to collaborate with cross‑functional teams and drive the implementation of Responsible AI practices, ideally within financial services or other regulated industries.
• You have a working knowledge of effective policies and processes around the usage of emerging AI tools and products, bringing best practices from the industry.
• You have a proven track record of solving complex problems, developing mitigation strategies, and influencing others on key AI initiatives.
• Y…