AI Engineer

Company Overview:

Westaim and CC Capital have joined forces to strategically transform Westaim from a holding company into a global alternative credit asset manager with a unique, integrated insurance platform, branded as The Westaim Corporation. This partnership supports a long-term vision to deliver innovative, customized financial solutions across alternative credit and insurance, creating scalable growth and meaningful client impact.

Ceres USA Holdings, LLC, part of the insurance platform within The Westaim Corporation strategy, is the parent company of Ceres Life Insurance—a fast-growing, technology-driven annuity carrier startup. Ceres is focused on redefining retirement security by combining modern fintech capabilities, top-tier talent, and strong vendor partnerships to deliver exceptional annuity solutions and digital experiences.

Ceres is deeply committed to a client-centered culture. Through its Digital Contact Center and advisor-facing platforms, the company delivers proactive, personalized, and technology-enabled support that empowers clients and advisors while maintaining the highest standards of trust, security, and regulatory compliance.

Position Summary
Reporting to the Chief Innovation Officer and working alongside the Head of Data Analytics and Head of Data Engineering, the Artificial Intelligence Engineer will design, develop, and deploy generative AI and machine‑learning solutions across Ceres Life’s core pipelines and customer‑facing tools. You will embed NLP/LLM capabilities for agent portals, application and onboarding, customer service chatbots, and predictive models, ensuring our AI initiatives deliver measurable business value and operational efficiency.

Key Responsibilities

Generative AI & ML Development

• Model Selection & Fine‑Tuning: Evaluate, select, and fine‑tune large language models and specialty AI frameworks (e.g., LLMs for document summarization, transformers for risk scoring).
• Prompt Engineering: Craft and optimize prompts for diverse use cases—automated eApp summarization, policy recommendation engines, conversational assistants.
• MLOps & Deployment: Build reproducible, scalable pipelines for model training, validation, monitoring, and versioning using tools like MLflow, Kubeflow, or SageMaker.

Integration & Automation

• API Development: Create robust APIs and microservices to surface AI capabilities (chatbots, document ingestion, predictive alerts) within the agent portal and internal dashboards.
• Workflow Automation: Partner with Operations & Customer Experience to automate tasks such as licensing checks, claims triage, and commission forecasting using AI‑driven workflows.
• Continuous Improvement: Instrument A/B tests and performance metrics to monitor model accuracy, latency, and user satisfaction; iterate on models and prompts accordingly.

Cross‑Functional Collaboration

• Data Partnership: Work closely with Data Engineering and Analytics teams to ensure high‑quality feature engineering, data preprocessing, and real‑time data access.
• Stakeholder Engagement: Translate technical possibilities into clear business cases for product, CX, and risk teams; present AI proofs‑of‑concept at Technology & Innovation Committee meetings.
• Ethics & Compliance: Embed AI governance practices—bias mitigation, privacy controls, audit trails—in accordance with industry regulations and internal policies.

Qualifications & Experience

• Technical Expertise: 5+ years designing and deploying machine‑learning and generative AI solutions in production; strong Python proficiency and experience with PyTorch or TensorFlow.
• LLM & NLP Skills: Hands‑on experience working with large language models (e.g., OpenAI, Anthropic, or open‑source alternatives), prompt engineering, and transformer architectures.
• MLOps Proficiency: Familiarity with CI/CD for ML, containerization (Docker/Kubernetes), and monitoring frameworks.
• Insurance/Financial Services Exposure: Prior experience in insurance, banking, or related domains preferred—understanding of annuity products, regulatory constraints, or risk modeling is a plus.
• Problem‑Solving & Communication: Strong analytical mindset with the ability to convey complex AI concepts to non‑technical stakeholders and drive adoption across teams.
• Education: Bachelor’s or Master’s in Computer Science, Machine Learning, Data Science, or related field.

Why Join Us?

• Innovation at Scale: Lead end‑to‑end AI initiatives in a high‑visibility role, shaping Ceres Life’s future as an insurtech pioneer.
• Collaborative Culture: Partner with seasoned executives and cross‑functional experts to deliver impactful AI solutions.
• Career Growth: Build the AI engineering function from the ground up, with opportunities for leadership and influence.
• Cutting‑Edge Technology: Work with the latest LLMs, MLOps tools, and cloud platforms to revolutionize the insurance experience.

If you’re passionate about harnessing generative AI to transform financial services and thrive in an entrepreneurial environment, we’d love to meet you.