Role Summary
We are looking for an AI / Agentic Engineer to design and build agentic middleware and workflow orchestration capabilities for enterprise insurance use cases. The engineer will focus on Agentic AI, MCP-based API wrapping, and cloud-native services on Azure PaaS using .
NET/Python. The role involves working across orchestration, workflow, and data layers to deliver resilient, production-grade solutions. Project management skills are a strong plus.
Key Responsibilities
- Design and implement agentic workflows and AI agents that support multi-step reasoning, tool use, and human-in-the-loop interactions.
- Build and maintain MCP wrappers around existing APIs, exposing them as MCP-compliant tools/resources for agent frameworks.
- Develop and enhance orchestration components that manage session context, route requests, and sequence calls across multiple workflows.
- Build backend services and integration components using .NET (C#) and/or Python on Azure PaaS (App Services, Logic Apps, Functions, data stores, messaging, security).
- Design and implement RESTful APIs and service endpoints for downstream and upstream consumer applications.
- Contribute to automated testing (unit, integration, and workflow-level) and uphold high standards for quality, reliability, and observability.
- Participate in solution design, technical documentation, and runbooks, supporting DevOps and production operations.
- Collaborate within a cross-functional pod (AI engineers, full-stack developers, DevOps, QA) to deliver features in iterative sprints.
- (Good to have) Provide light project management support—planning, tracking milestones, managing risks/dependencies, and reporting status to stakeholders.
Required Skills & Experience
Agentic AI & AI Engineering
Strong hands-on experience designing and implementing agentic AI solutions: multi-step workflows, tool-calling, and orchestration.
Experience with AI agents and orchestration frameworks (e.g., Claude-based agents, Lang Chain, Vertex AI Agent Builder, Auto Gen, google ADK or similar).
Ability to define agent behavior, tool boundaries, and logging/audit needs for enterprise deployments.
MCP (Model Context Protocol)
Practical understanding of Model Context Protocol (MCP) concepts for connecting agents to external data sources and APIs.
Experience building or consuming MCP servers to provide live context to agents from databases, internal tools, and document stores.
Familiarity with MCP primitives (tools/resources/prompts) and integrating MCP with agentic frameworks.
Backend Engineering – .NET/Python & Azure PaaS
Strong programming skills in .
NET (C#) and/or Python for building production-grade services and APIs.
Hands-on experience with Azure PaaS services such as App Services, Functions, Azure SQL/Cosmos DB, Storage, Service BEvent Hub, Key Vault, and monitoring.
Solid experience designing and consuming RESTful APIs, including authentication/authorization (OAuth2.0 / JWT / OIDC).
Strong grounding in software engineering best practices: Git, CI/CD, automated testing, observability, and secure coding.
General
Experience working in Agile / Scrum teams on complex, multi-sprint delivery programs.
Excellent communication and collaboration skills with distributed, cross-functional teams.
Nice-to-Have (Project Management & Domain)
Experience acting as a tech lead or project lead—backlog grooming, sprint planning, and coordination across engineering, business, and QA.
Prior experience in insurance or financial services, especially quote/bind, NTU, and policy servicing workflows.
Experience with AI-assisted development tools (e.g., Claude Code, GitHub Copilot, or similar).
Familiarity with RAG, LLM integrations, or broader AI/ML platform engineering (Databricks, vector search, etc.).