Ingestion Principal Engineer

Chubb•Jersey City, NJ

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

15+ years of proven experience designing and implementing global platform solutions at scale
Strong background in software engineering, cloud platforms (AWS, Azure, GCP), APIs, microservices, event-driven architecture, and data management
Hands-on experience with durable execution / workflow orchestration engines — Temporal (preferred), Camunda, AWS Step Functions, or Cadence — for long-running, fault-tolerant business processes
Practical experience building or architecting agentic AI systems: agent orchestration frameworks (LangGraph, AutoGen, CrewAI, Claude Agent SDK), tool/function calling, Model Context Protocol (MCP), RAG pipelines, and agent evaluation/guardrail design
Knowledge graphs and semantic technologies: Neo4j, MongoDB, GraphDB, ontologies, semantic data modeling/JSON-LD, graph query languages (Cypher, SPARQL, Gremlin)
AI/ML platforms: Azure OpenAI, AWS Bedrock, Google Vertex AI, Anthropic Claude API, and MLOps/LLMOps practices (prompt versioning, evaluation, observability, cost/latency management)
Deep understanding of distributed systems fundamentals: consistency models, idempotency, retries/backoff, circuit breakers, saga patterns, and observability (structured logging, distributed tracing, correlation IDs)
Strong understanding of insurance processes, regulatory requirements, and industry standards
Proven experience leading technical teams and managing cross-functional projects in an agile environment
Experience with JIRA, Service Now, Clarity, and Azure DevOps
Bachelor's and/or Master's degree in a technical or related discipline required

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