Senior AI Engineer - GenAI, insurance or reinsurance, MLOps, Python/PySpark
Contract Type: Freelance (B2B)
Duration: 6-12 months initial contract, extension possible
Daily rate: Negotiable
The AI Engineer is responsible for engineering, operationalizing, and governing AI solutions in production. While the role requires strong exposure to data science and model behavior, it does not require deep Data Scientist specialization. The focus is on turning models and experiments into reliable, well-governed production systems.
Responsibilities
* Own and maintain prompt engineering strategies, including prompt versioning, testing, and optimization
* Design AI workflows combining 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 behaviour
MLOps
* Support building and maintaining production-grade deployment pipelines for AI solutions
* Ensure reliability, scalability, cost control, and latency optimisation
* Implement monitoring and observability for AI systems (usage, performance, drift, failures)
* Define and enforce change control, versioning, rollback, and release management processes
Collaboration with Data Science & Business
* Collaborate closely with data scientists, actuaries, and other business functions
* Validate model behaviour, outputs, and assumptions from a production and business-use perspective
* Communicate engineering limitations and operational considerations to stakeholders
Required Skills & Experience
Core Skills
* 5+ years of experience in AI/ML engineering, advanced analytics, or advanced software engineering roles
* 2+ years hands-on experience building, calibrating, and operationalising AI/ML solutions
* Strong algorithmic and problem-solving skills
* Strong programming skills in Python / PySpark and strong SQL expertise
* Exposure to Data Science methods for validating AI models
* Palantir Foundry and AIP experience
LLM & Advanced AI Capabilities
* Hands-on experience with prompt engineering, prompt testing, and prompt lifecycle management
* Experience implementing RAG architectures or similar approaches
* Experience with AI orchestration frameworks, agentic patterns, and tool / function calling
MLOps
* Strong understanding of model evaluation, calibration techniques, and monitoring
* Familiarity with model explainability, fairness, and robustness
* Experience with MLOps tooling and practices
Platforms & Tools
* 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)
Nice to Have
* 1–2 years exposure to insurance or reinsurance
* Experience with agentic AI frameworks and enterprise-scale AI platforms
* Experience working in insurance / reinsurance (Underwriting, Claims, Inforce management for L&H)
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