Engineer III - App Engg & AI

Role Overview

Responsibilities

• Build LLM-enabled features, RAG pipelines, agentic workflows, intelligent automation, and model or API integrations.
• Develop backend services, APIs, user-facing components, data integrations, and cloud-native deployment assets.
• Implement prompt templates, grounding, structured outputs, tool calling, context management, model routing, and evaluation harnesses.
• Create secure enterprise connectors and develop comprehensive software and AI-quality tests.
• Add operational telemetry, diagnostics, usage controls, runbooks, and secure engineering controls.
• Deliver sprint commitments, participate in reviews, resolve defects, and document technical and operational guidance.

Required Qualifications

• 3 to 5+ years of software engineering experience, including at least 1 year building AI/ML or LLM-integrated applications.
• Strong Python development skills or equivalent proficiency in a language used for enterprise AI applications.
• Experience with REST APIs, asynchronous processing, authentication, data access, testing, Git, and CI/CD.
• Practical experience with LLM SDKs or APIs, prompt orchestration, RAG, vector retrieval, tool calling, and structured outputs.
• Experience deploying applications on a major cloud platform and troubleshooting across application, model, integration, and data layers.
• Ability to write maintainable production-ready code, participate in peer reviews, and work in short iteration cycles.
• Working knowledge of privacy, secure coding, and responsible AI controls for enterprise applications.

Preferred Qualifications

• Experience with Azure AI Foundry, Azure OpenAI, Anthropic Claude, Model Context Protocol, or comparable platforms and frameworks.
• Experience with full-stack frameworks, containers, serverless services, API management, event-driven integration, and observability tools.
• Familiarity with evaluation frameworks, synthetic test generation, red-team testing, and LLMOps practices.
• Experience integrating work-management, IT service-management, risk, compliance, or enterprise knowledge platforms.
• Experience in financial services, lending, auto finance, compliance, risk, or another regulated environment.
• Knowledge of SQL, data engineering, semantic layers, vector databases or search, or knowledge graphs.