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Chubb

Global property & casualty insurer

Senior Software Engineer

AI Application Engineering +1Updated on Nov 13
Full-timeJersey City, NJ, USAIn-person

About the Job

Requirements

  • At least 8 years of software engineering experience, including at least 3 years building distributed, data-intensive, or platform systems in production.
  • A Bachelor's or Master's degree in Computer Science, Engineering, or a related field, or equivalent experience.
  • Strong programming skills in Python, Java, Scala, or a similar language, and strong SQL skills; experience with microservices, APIs, and event-driven architecture on AWS, Azure, or GCP.
  • Solid distributed-systems fundamentals, including idempotency, retries and backoff, circuit breakers, consistency, structured logging, distributed tracing, and correlation IDs.
  • Experience with streaming technologies such as Kafka, Kinesis, or Event Hubs; distributed data processing such as Spark, Flink, or Beam; and data modeling for SQL and NoSQL stores.
  • Hands-on experience with LLM-based applications, including at least one production or serious prototype using RAG or agents with tool calling.
  • Working knowledge of ontologies or knowledge graphs, data science, and machine-learning basics, including the Python data stack, model evaluation, and how models are deployed and monitored.
  • Hands-on CI/CD experience building and maintaining Jenkins pipelines with automated test, scan, and release stages, and Git workflows with pull requests.
  • Strong code-review experience, both providing and receiving reviews, and applying standards for correctness, security, testing, and readability.

Responsibilities

  • Design and build scalable services and APIs with clear contracts, idempotency, retries, and failure isolation; take features from user stories and acceptance criteria through production in an agile software development lifecycle.
  • Contribute to design and architecture reviews, propose improvements to standards and tooling, and write clean, testable, observable code with strong unit, integration, and contract tests.
  • Integrate with internal systems and external partners through governed APIs, event streams, and webhooks, with schema versioning.
  • Build durable workflows and agentic AI features, including human-in-the-loop steps, tool calling, MCP, and guardrails.
  • Evaluate and monitor AI features using prompt versioning, evaluation sets, tool-call accuracy, task success, cost, latency, and human review gates.
  • Build retrieval-augmented generation, memory, ontology, and document capabilities, including ingestion, chunking, embeddings, vector and hybrid search, reranking, retrieval evaluation, and structured knowledge extraction.
  • Protect retrieval and AI inputs with document access control, personally identifiable information/payment card industry redaction, and defenses against prompt injection, while following security, privacy, and regulatory requirements.
  • Build and maintain CI/CD pipelines; manage branching and release practices; review code thoroughly; keep pipelines healthy; resolve root causes; mentor engineers; and improve cloud-native automation where useful.
  • Own features end to end, from design through production, and help shape technical direction within the team.
  • Partner with architects, data scientists, product owners, and business stakeholders to deliver solutions in an insurance environment.

Desired Qualifications

  • Knowledge of or experience with insurance processes, regulatory requirements, and industry standards.
  • Experience with Kubernetes, Docker, Terraform, or GitOps.
  • Experience with Temporal, Camunda, AWS Step Functions, or Cadence.
  • Experience with Delta Lake, Iceberg, data governance, or metadata management.
  • Experience with LangGraph, AutoGen, CrewAI, Claude Agent SDK, MCP, and LLM evaluation or observability tools.
  • Experience with Neo4j, MongoDB, GraphDB, JSON-LD, SHACL, Cypher, SPARQL, or Gremlin.
  • Experience with SonarQube, dependency and container scanning, static or dynamic application security testing, Artifactory, or Nexus.
  • Additional depth in AI/ML platforms such as Azure OpenAI, AWS Bedrock, Google Vertex AI, Anthropic Claude API, MLflow, Azure Machine Learning, or SageMaker.

About the Company

Chubb

Global property & casualty insurer

Chubb is the world’s largest publicly traded property and casualty insurer, offering commercial and personal insurance, reinsurance, life and health products across 54 countries. It underwrites policies by evaluating risk, pricing premiums, and paying claims fairly and promptly when covered events occur. Its breadth of products, extensive distribution, and strong financial position distinguish it from competitors and enable it to serve diverse clients globally. Its goal is to help people and businesses manage risk with clear policy terms and reliable financial protection.

Company size
10,001+
Company stage
IPO
Headquarters
Zurich, Switzerland
Founded
1985

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