Own and maintain prompt engineering strategies, including prompt versioning, testing, and optimization
Design AI workflows that combine models, prompts, tools, enterprise data, and business logic
Implement AI orchestration layers to manage multi-step reasoning, decisioning, and actions
Ensure AI systems integrate cleanly into business workflows, APIs, and user interfaces
Apply guardrails to ensure safe, explainable, and compliant AI behavior
Support in building and maintaining production-grade deployment pipelines for AI solutions
Ensure reliability, scalability, cost control, and latency optimization
Implement monitoring and observability for AI systems (usage, performance, drift, failures)
Define and enforce change control, versioning, rollback, and release management processes
Collaborate closely with data scientists, actuaries and other business functions
Validate model behavior, outputs, and assumptions from a production and business-use perspective

5+ years of experience in AI/ML engineering, advanced analytics, or advanced software engineering roles
Strong algorithmic and problem-solving skills
Strong programming skills in Python/PySpark and strong SQL expertise
Exposure to Data Science methods in validating AI models
Palantir Foundry and AIP experience
Hands-on experience with prompt engineering, prompt testing, and prompt lifecycle management
Experience implementing RAG architectures and similar approaches
Experience with AI orchestration frameworks, agentic patterns, and tool/function calling
Strong understanding of model evaluation, calibration techniques, and monitoring
Familiarity with model explainability, fairness, and robustness
Experience with MLOps tooling and practices
Experience working in cloud environments (AWS, Azure, or GCP)
Experience integrating AI models into production systems with monitoring, logging, and alerting
Experience working with large data sets on enterprise data platforms and distributed computing (Spark/Hive/Hadoop preferred)

AI Engineer – Life & Health Re

Key skills