Job Summary
The Senior AI Engineer will join an AI Platform Team focused on building secure, scalable, and reusable enterprise AI capabilities. The role involves enabling safe and rapid AI adoption across the enterprise by delivering governed platform capabilities, reusable patterns, and production-ready AI solutions, including Retrieval-Augmented Generation (RAG)-based search, chat assistants, and agent/chatbot services. This hands-on engineering position emphasizes backend and platform engineering, cloud-native development, and the delivery of enterprise-grade AI solutions.
Key Responsibilities
• Manage the full solution lifecycle, including infrastructure as code, APIs and services, cloud deployment, data storage, and production-ready delivery.
• Build reusable AI platform components and domain-specific AI solutions within established privacy, security, compliance, observability, and engineering standards.
• Develop backend services, platform capabilities, and cloud-native delivery solutions.
• Support the development of search agents, navigator agents, and domain-specific chatbots for areas such as benefits, claims, and membership.
• Create reusable base prompt templates and AI platform assets for downstream teams.
• Build and deploy enterprise-grade APIs and services that integrate AI capabilities into business workflows.
• Apply AI safety controls and output validation to support reliable and secure AI solutions.
Required Qualifications
• 8+ years of software engineering experience, including hands-on development in modern application engineering.
• Primary expertise in Node.js and TypeScript.
• Experience building backend- and platform-oriented solutions, including APIs, services, databases, cloud deployment, and operational support.
• Hands-on AWS experience with services such as API Gateway, Lambda, Amazon Bedrock, S3, EventBridge, DynamoDB, PostgreSQL, CloudWatch, AWS CDK, and Fargate.
• Experience with Amazon Bedrock is required.
• Experience with infrastructure as code (IaC), specifically AWS CDK.
• 1+ year of hands-on, production-level experience building Generative AI solutions, particularly RAG/search-based AI, chatbots, or copilot experiences. Personal projects alone do not meet this requirement.
• Practical understanding of prompt engineering and its impact on output quality.
• Working knowledge of embeddings, chunking, semantic retrieval, and vector search.
• Experience building and deploying enterprise-grade APIs and services that integrate AI capabilities into business workflows.
• Knowledge of software engineering fundamentals, including testing, debugging, source control, and CI/CD.
• Enterprise-level software engineering experience.
Preferred Qualifications
• Experience with Python.
• Experience with agentic solution design, orchestration frameworks, or tool-using AI workflows.
• Experience with Azure in addition to AWS.
• Familiarity with AI evaluation, observability, tracing, benchmarking, or monitoring for Generative AI solutions.
• Experience working in regulated environments such as healthcare, insurance, or financial services.
• Experience contributing to reusable platform components, internal SDKs, or service catalogs.
• Experience with event-driven architecture, enterprise integrations, or cloud-native service patterns.
