Senior AI Polyglot Engineer

MSIG Holdings•Warren, NJ

About The Position

MSIG USA is seeking a Senior AI Polyglot Engineer for a product domain team within its Commercial Property & Casualty insurance business, supporting areas such as Underwriting, Claims, Finance, and Reinsurance. The role combines broad software engineering with agentic development practices: the engineer directs AI coding agents to accelerate delivery while retaining accountability for solution design, correctness, security, maintainability, and production readiness. The engineer shares end-to-end ownership of domain technology capabilities, from understanding business needs and designing solutions through implementation, deployment, production support, and continuous improvement. Work spans applications, user experiences, services, integrations, databases, data pipelines, automation, and supporting Azure infrastructure. The role is organized around business capabilities rather than technology layers and involves close collaboration with business stakeholders, product colleagues, adjacent domain teams, and shared platform teams. The technology stack includes .NET/C#, React, SQL, Azure, Python, and data integration and orchestration technologies including Azure Data Factory. Agentic software development is central to delivery: the engineer directs AI coding agents through planning, implementation, testing, and troubleshooting, independently validates their output, and protects sensitive information through approved tools, least privilege, secure credential handling, and appropriate human approvals.

Requirements

Seven or more years of professional software engineering experience delivering and supporting production systems.
Demonstrated ownership of business capabilities across multiple technical layers, rather than experience confined to a single development specialty.
Strong hands-on development skills in .NET/C# and React, with practical Python experience for automation, integrations, or data processing.
Strong SQL skills covering relational design, query optimization, transactions, data integrity, and troubleshooting.
Experience developing and operating solutions on Azure, including building and maintaining Azure Data Factory pipelines.
Demonstrated hands-on experience using AI coding agents beyond autocomplete for complex, multi-file development, automated testing, and iterative debugging.
Experience orchestrating agentic development workflows, including task decomposition, effective prompting, architectural guardrails, and independent validation of AI-generated artifacts.
Understanding of API design, distributed systems, automated testing, security, Git, CI/CD, and production diagnostics.
Ability to learn unfamiliar technologies and domain concepts, work through ambiguity, and communicate technical decisions clearly.
A degree in computer science, engineering, or a related discipline, or equivalent practical experience.

Nice To Haves

Experience in Commercial Property & Casualty insurance, particularly Underwriting, Claims, or Finance, or in other regulated business environments.
Experience working in cross-functional product teams with ongoing responsibility for both delivery and operation of their systems.
Experience modernizing established applications and connecting transactional systems with data-processing platforms.
Experience with advanced agentic development practices, including repository-level instructions, reusable agent skills, MCP integrations, and multi-agent workflows.

Responsibilities

Own engineering work within the assigned domain, from business discovery and solution design through release, production support, and ongoing improvement.
Develop an understanding of domain workflows, business rules, data, controls, and dependencies, and use that understanding to make sound technical decisions.
Deliver complete capabilities across user interfaces, services, APIs, databases, integrations, data pipelines, and supporting Azure infrastructure.
Collaborate with product and business stakeholders to clarify requirements, define acceptance criteria, prioritize improvements, and evaluate business outcomes.
Translate requirements into bounded agent-executable tasks, providing relevant context, architectural constraints, repository conventions, and verification criteria.
Direct AI coding agents in codebase exploration, implementation, testing, debugging, and documentation, while independently validating their output.
Build reliable applications, integrations, and data movement workflows with appropriate validation, reconciliation, error handling, recovery, observability, and auditability.
Lead technical design decisions, evaluate trade-offs, and recommend practices that improve reliability, maintainability, and delivery effectiveness.
Maintain and improve existing domain systems by addressing technical debt, performance issues, operational failures, and changing business requirements.
Coordinate contracts and dependencies with other domain and platform teams while following enterprise architecture, security, and governance standards.
Protect sensitive information and control agent access through approved tools, least privilege, secure credential handling, and appropriate human approvals.