AI Engineer

Role Overview We are looking for a Senior AI Engineer with 4+ years of experience to lead the design and implementation of enterprise AI solutions on AWS. This role will focus on architecting and building scalable chatbot platforms, advanced RAG systems, agentic AI workflows, multiagent solutions, and business process automation. The ideal candidate should have strong hands-on engineering experience, a solid understanding of GenAI application architecture, and the ability to move solutions from proof of concept into secure, maintainable, production-ready systems. Key Responsibilities Lead the architecture, design, and development of AI-powered applications on AWS using Amazon Bedrock and related cloud-native services. Build and productionize enterprise chatbot platforms with retrieval, citations, tool use, orchestration, and integrations with internal business systems. Design advanced RAG pipelines for enterprise data, including ingestion, retrieval, ranking, grounding, and response quality improvement. Develop agentic workflows and multi-agent systems for complex, multi-step business processes. Design and implement action-based integrations with APIs, Lambda functions, databases, internal services, and workflow tools. Establish best practices for prompt design, LLM integration, evaluation, observability, retries, fallback handling, and deployment patterns. Lead automation initiatives using AI and non-AI approaches depending on business fit and operational reliability. Mentor junior engineers and review designs, implementations, and technical decisions. Work with stakeholders to identify high-value AI use cases and convert them into scalable solutions. Partner with platform, cloud, and security teams to ensure production readiness, access control, and operational stability. Required Qualifications 4+ years of experience in software engineering, backend engineering, AI engineering, machine learning engineering, or related roles. Strong hands-on experience with AWS

services such as Bedrock, Lambda, API Gateway, S3, DynamoDB, CloudWatch, Step Functions, IAM, and eventdriven/serverless architectures. Proven experience building production-grade chatbot or GenAI applications. Strong experience with RAG architecture, embeddings, retrieval strategies, vector stores, and grounded response generation. Experience designing agentic workflows, tool-calling systems, or multi-agent solutions. Strong programming skills in Python. Working experience with Node.js and/or TypeScript. Experience designing robust API integrations and enterprise service interactions. Strong understanding of system design, reliability, observability, and scalable backend architecture. Experience with CI/CD, code quality practices, and cloud deployment workflows. Preferred Qualifications Experience with Amazon Bedrock Agents, Knowledge Bases, and action groups. Experience with LangGraph, LangChain, Semantic Kernel, or comparable orchestration tools. Experience with OpenSearch or other vector/search infrastructure. Familiarity with authentication, authorization, and enterprise integration patterns. Experience designing evaluation frameworks for LLM applications. Experience with guardrails, hallucination reduction, and response quality controls. Experience leading small teams or owning technical direction for AI products. Familiarity with workflow automation tools and operational process automation. What This Role Will Work On Production-grade enterprise AI assistants Multi-agent and agentic workflow systems RAG architecture for internal enterprise knowledge AI-enabled and rule-based business process automation AWS-native AI platforms and reusable architecture patterns