Senior Software Engineer

Role Summary

Builds and operates the core APIs, services, orchestration layers, integrations, and business capabilities. This role combines strong software engineering discipline with agentic development practices to deliver secure, scalable, resilient services from design through production and operation.

Key Responsibilities

• Design, build, test, deploy, and operate cloud-native backend services, APIs, workflows, and integration capabilities.
• Implement business logic, orchestration services, domain services, event-driven patterns, and service composition required by project workstreams.
• Develop integrations with enterprise systems, third-party platforms, data services, pricing/underwriting capabilities, and AI/agent services.
• Leverage AI coding agents and engineering copilots to accelerate development while maintaining strong review, testing, and production quality practices.
• Create automated unit, integration, contract, regression, and performance tests as part of the delivery lifecycle.
• Contribute to API standards, reusable patterns, golden paths, CI/CD pipelines, infrastructure automation, and service reliability practices.
• Own production readiness, monitoring, incident response, defect remediation, and continuous improvement for delivered services.
• Collaborate with Analysts and Product Owners to ensure requirements, contracts, and acceptance criteria are clear and technically executable.

Preferred Experience / Capabilities

• Backend development experience with Java, Python, .NET, Node.js, TypeScript, or equivalent enterprise technologies.
• API-first design, microservices, service orchestration, event-driven architecture, and distributed systems patterns.
• AWS cloud services, containers, CI/CD, infrastructure as code, secrets management, and automated deployment practices.
• Experience with contract testing, automated quality gates, performance tuning, observability, and production support.
• Comfortable working in an AI-assisted delivery environment where engineers guide, review, harden, and operationalize agent-generated outputs.
• Design and maintain ontologies, taxonomies, business vocabularies, semantic models, and concept relationships across domains.
• Develop knowledge graphs, entity relationships, metadata structures, and mappings that allow agents and systems to reason across business concepts.
• Engineer AI agent patterns, retrieval-augmented generation pipelines, prompt strategies, orchestration flows, evaluation frameworks, and reusable AI components.
• Generative AI, LLM application development, prompt engineering, agent orchestration, and RAG architecture.
• Ontology modeling, taxonomy development, knowledge graphs, semantic technologies, and metadata design.
• Python, ML/AI frameworks, vector databases, semantic search engines, and data integration patterns.

Differentiators

• Not a narrow coder role; expected to shape the service architecture and own outcomes through production.
• Understands how to reduce dependencies through strong contracts and self-service platform patterns.