As a Senior Software Engineer within our Ingestion Platform team here at Chubb, you will help rebuild how digital products are delivered to customers and partners worldwide. You will design and build the services, workflows, AI capabilities, and data pipelines that power that platform, and you will raise the technical bar for the engineers around you. As a key contributor on our team, you will own features end to end, from design through production, and who helps shape technical direction within your team. You will partner closely with architects, data scientists, product owners, and business stakeholders to deliver solutions in an insurance environment where reliability, privacy, security, and regulatory discipline are just as important as speed. With us, you will have the opportunity to directly shape core platform decisions, architect and deliver systems that scale, helping to define how we build and operate digital experiences with greater intelligence, resilience, and precision.
In this role, you will:
- Design and build scalable services and APIs with clear contracts, idempotency, retries, and failure isolation, and take features from user stories and acceptance criteria to production in an agile SDLC
- 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 using tools like Temporal, Camunda, Step Functions, LangGraph, AutoGen, CrewAI, or the Claude Agent SDK, including human-in-the-loop steps, tool calling, MCP, and guardrails
- Evaluate and monitor AI features with prompt versioning, evaluation sets, tool-call accuracy, task success, cost, latency, and human review gates
- Build RAG, 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, PII/PCI 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 it helps
- 8+ years of software engineering experience, including 3+ years building distributed, data-intensive or platform systems in production; knowledge of and/or experience with insurance processes, regulatory requirements and industry standards is a plus
- Bachelor's or Master's degree in Computer Science, Engineering or a related field (or equivalent experience)
- Strong programming in Python, Java, Scala or similar, and strong SQL, with experience of microservices, APIs and event-driven architecture on AWS, Azure or GCP; experience with Kubernetes, Docker, Terraform, and/or GitOps is a plus
- Solid distributed systems fundamentals: idempotency, retries and backoff, circuit breakers, consistency, structured logging, distributed tracing and correlation IDs; experience with Temporal, Camunda, AWS Step Functions, and/or Cadence is a plus
- Experience with streaming (Kafka, Kinesis or Event Hubs) and distributed data processing (Spark, Flink or Beam), and with data modelling for SQL and NoSQL stores; experience with Delta Lake, Iceberg, and data governance and/or metadata management is a plus
- Hands-on experience with LLM-based applications including at least one production or serious prototype using RAG (chunking, embeddings, vector search) or agents with tool calling; experience with LangGraph, AutoGen, CrewAI, Claude Agent SDK, MCP, and LLM evaluation and/or observability tools is a plus
- Working knowledge of ontologies or knowledge graphs, and of data science and ML basics (Python data stack, model evaluation, how models are deployed and monitored); experience with Neo4j, MongoDB, GraphDB, JSON-LD, SHACL, Cypher, SPARQL, and/or Gremlin is a plus
- Hands-on CI/CD experience building and maintaining Jenkins pipelines (Jenkins file, shared libraries) with automated test, scan and release stages, and Git workflows with pull requests; experience with SonarQube, dependency and container scanning, SAST/DAST, and/or Artifactory or Nexus isa plus
- Strong code review experience, both providing and receiving reviews, as well as applying standards for correctness, security, testing and readability
- Additional depth in AI/ML platforms such as Azure OpenAI, AWS Bedrock, Google Vertex AI, Anthropic Claude API, MLflow, Azure Machine Learning, or SageMaker is a plus
The pay range for the role is $150,000 to $205,000. The specific offer will depend on an applicant’s skills and other factors. This role may also be eligible to participate in a discretionary annual incentive program. Chubb offers a comprehensive benefits package, more details on which can be found on our careers website. The disclosed pay range estimate may be adjusted for the applicable geographic differential for the location in which the position is filled.
About UsSkills Required
- 8+ years of software engineering experience, including 3+ years building distributed, data-intensive, or platform systems in production
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field, or equivalent experience
- Strong programming experience in Python, Java, Scala, or similar, plus strong SQL
- Experience with microservices, APIs, and event-driven architecture on AWS, Azure, or GCP
- Distributed systems fundamentals including idempotency, retries, backoff, circuit breakers, consistency, structured logging, distributed tracing, and correlation IDs
- Experience with streaming technologies such as Kafka, Kinesis, or Event Hubs
- Experience with distributed data processing such as Spark, Flink, or Beam
- Experience with SQL and NoSQL data modeling
- Hands-on experience with LLM-based applications, including production or serious prototype experience with RAG or agent tool calling
- Working knowledge of ontologies or knowledge graphs and data science and machine learning fundamentals
- Hands-on CI/CD experience building and maintaining Jenkins pipelines with automated testing, scanning, and release stages
- Git workflow experience using pull requests
- Strong code review experience and ability to apply standards for correctness, security, testing, and readability
- Knowledge of or experience with insurance processes, regulatory requirements, and industry standards
- Experience with Kubernetes, Docker, Terraform, and/or GitOps
- Experience with Temporal, Camunda, AWS Step Functions, and/or Cadence
- Experience with Delta Lake, Iceberg, data governance, and/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, and/or Gremlin
- Experience with SonarQube, dependency and container scanning, SAST/DAST, and/or Artifactory or Nexus
- Additional experience with Azure OpenAI, AWS Bedrock, Google Vertex AI, Anthropic Claude API, MLflow, Azure Machine Learning, or SageMaker
Chubb Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Chubb and has not been reviewed or approved by Chubb.
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Healthcare Strength — Healthcare coverage includes multiple medical plan options with preventive care, plus dental and vision, alongside HSAs/FSAs, telemedicine, and wellness resources. The breadth of offerings is presented as comprehensive for a large insurance employer.
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Retirement Support — A 401(k) plan with company contributions anchors the financial benefits, complemented by life and disability insurance. These programs reinforce long-term savings and protection.
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Strong & Reliable Incentives — Performance-based and year-end bonuses are part of the total rewards, with structured reviews supporting incentive opportunities. These components provide compensation beyond base salary.
Chubb Insights
What We Do
Chubb is the world’s largest publicly traded property and casualty insurance company. With operations in 54 countries and territories, Chubb provides commercial and personal property and casualty insurance, personal accident and supplemental health insurance, reinsurance and life insurance to a diverse group of clients. As an underwriting company, we assess, assume and manage risk with insight and discipline. We service and pay our claims fairly and promptly. The company is also defined by its extensive product and service offerings, broad distribution capabilities, exceptional financial strength and local operations globally. Parent company Chubb Limited is listed on the New York Stock Exchange (NYSE: CB) and is a component of the S&P 500 index. Chubb maintains executive offices in Zurich, New York, London, Paris and other locations, and employs 31,000 people worldwide. Additional information can be found at: chubb.com.







