Ingestion Principal Engineer
About The Position
In this high-impact, high-visibility role, you will lead the planning, solution design, and end-to-end software development and testing for Chubb's global digital enablement platform. You will be at the forefront of driving strategic technical directions including agentic AI adoption, durable workflow orchestration, and event-driven microservices architecture — and overseeing delivery of new and enhanced product features critical to our business. You will collaborate closely with architecture, data, engineering, and business teams, enabling effective decision-making and ensuring that all efforts align with business objectives, regulatory requirements, and industry best practices. Your proven ability to lead transformative and strategic technology initiatives, combined with deep technical expertise in distributed systems, AI/agentic architectures, and the insurance domain, will be essential. Your extensive experience working with process and engineering teams in an agile environment will position you deliver impactful results and elevate the platform's capabilities.
Requirements
- Proven ability to lead transformative and strategic technology initiatives
- Deep technical expertise in distributed systems
- Deep technical expertise in AI/agentic architectures
- Deep technical expertise in the insurance domain
- Extensive experience working with process and engineering teams in an agile environment
Nice To Haves
- Experience with Temporal (or equivalent durable execution engines)
- Experience with multi-agent orchestration frameworks (LangGraph, AutoGen, CrewAI, Claude Agent SDK)
- Experience with Model Context Protocol (MCP)
- Experience with MLOps/LLMOps practices
- Experience with prompt/version management
- Experience with evaluation harnesses
- Experience with model routing across tiers
- Experience with cost/latency monitoring
- Experience with human-review gates for AI-generated outputs
- Experience with secure handling of PII/PCI data
- Experience with auditability of AI agent decisions
- Experience with defense against prompt injection and other agentic-specific threat vectors
- Experience with contract testing and schema versioning
- Experience with cloud-native and serverless computing
Responsibilities
- Own the platform vision and technical strategy, ensuring alignment with business objectives and delivering measurable value to stakeholders
- Develop and maintain the platform roadmap, balancing feature delivery, enhancements, and technical improvements — including modernization toward event-driven, API-first, and agentic architectures — to drive continuous innovation
- Define and enforce architectural standards for distributed systems: service decomposition, API contracts, idempotency, durable execution, and failure isolation
- Guide development teams by setting code standards, conducting design/architecture reviews, and embedding best practices in software engineering (clean architecture, testability, observability-by-design)
- Design and oversee durable workflow orchestration using Temporal (or equivalent durable execution engines) for long-running, stateful business processes spanning policy, claims, and billing systems — including saga patterns, compensating transactions, and human-in-the-loop steps
- Architect and govern agentic AI systems: multi-agent orchestration frameworks (LangGraph, AutoGen, CrewAI, Claude Agent SDK), tool-use/function-calling patterns, the Model Context Protocol (MCP) for tool and context interoperability, agent memory/state management, and guardrails for autonomous decision-making
- Plan and oversee project timelines, resource allocation, and technical deliverables for platform enhancements and new features within an agile SDLC
- Design and manage integration with internal systems (policy, claims, billing, CTM) and external partners (vendors, third-party data sources) via well-governed APIs, event streams, and webhooks — with contract testing and schema versioning
- Evaluate and implement emerging technologies — agentic AI, workflow orchestration engines (Temporal, Camunda, Step Functions), automation, cloud-native and serverless computing — to improve platform efficiency, resilience, and scalability
- Establish MLOps/LLMOps practices for AI-driven features: prompt/version management, evaluation harnesses, model routing across tiers, cost/latency monitoring, and human-review gates for AI-generated outputs
- Ensure the platform meets regulatory, data privacy, and cybersecurity standards, including secure handling of PII/PCI data, auditability of AI agent decisions, and defense against prompt injection and other agentic-specific threat vectors
- Lead successful delivery of enhancements and new product introductions in cooperation with all internal partners
- Lead troubleshooting and root-cause resolution of platform and workflow-orchestration issues, using distributed tracing and structured logging to minimize business disruption
- Partner with business product owners, enterprise architects, and product team members to document and groom product features, user stories, and acceptance criteria (Given/When/Then) in an agile development environment
- Work with technical experts to ensure technical designs align with business needs and comply with enterprise IT policies, best practices, standards, and processes
- Manage day-to-day technical activities and mentor engineers on distributed systems and AI/agentic design patterns
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What This Job Offers
Job Type
Full-time
Career Level
Principal
Education Level
No Education Listed
