AI Cloud Engineer

Experience: 3-5 years Pay: $55-$65 per hour on W2, depending on experience (No C2C) Build and deploy enterprise-scale agentic AI solutions supporting business workflows, decision support, operational intelligence, and customer engagement Hands-on engineering role delivering production-grade AI agents using AWS Bedrock, Amazon Bedrock AgentCore, and governed cloud-native architectures Partner with architects, data teams, product owners, and Responsible AI stakeholders Key Responsibilities Develop cloud-native microservices, APIs, and event-driven components using Python, JavaScript/TypeScript, FastAPI, AWS Lambda, and EventBridge Build and deploy enterprise AI agents using Amazon Bedrock AgentCore, Bedrock models, AgentCore Gateway, and agent-to-agent communication Implement data ingestion, embeddings, vector search, semantic retrieval, knowledge graph, and memory pipelines Develop intent classification, tool routing, workflow orchestration, guardrails, and human-in-the-loop escalation patterns Integrate agents with enterprise systems such as Salesforce, Genesys, Denodo, APIs, MCP tools, and event streams Build evaluation, monitoring, and tracing for agents, including quality metrics, hallucination and safety checks, latency, and cost Uphold enterprise standards for security, IAM, data protection, auditability, Responsible AI, and production reliability Lead implementation of specific agent workstreams and mentor associate and mid-level engineers Required Qualifications 3-5 years of software engineering experience delivering cloud-native applications or AI/ML-enabled platforms Strong proficiency in Python and JavaScript/TypeScript, including API development, async processing, test automation, and production debugging Experience with microservices, APIs, event-driven workflows, and secure enterprise integrations Hands-on AWS experience: serverless, containers, messaging/eventing, IAM, observability, and cloud-native deployment Recent experience building enterprise GenAI or agentic AI solutions, including agents, agentic RAG, and multi-step orchestration Experience with Amazon Bedrock, Amazon Bedrock AgentCore, or comparable LLM and agent runtime platforms Experience with LangGraph, LangChain, Strands, MCP, A2A protocols, or comparable multi-agent frameworks Experience with model evaluation, prompt engineering, agent quality testing, and LLM-as-judge patterns Experience with vector databases, embeddings, semantic search, knowledge bases, and memory stores Experience implementing AI guardrails, safety controls, access controls, audit logging, and human escalation paths Strong understanding of application security, data governance, scalability, and production operations Preferred Qualifications Experience with AWS EventBridge, MSK, SNS/SQS, Step Functions, API Gateway, and container services Experience delivering AI or data products in financial services, insurance, or other regulated environments Familiarity with enterprise data products, semantic layers, Denodo, knowledge graphs, and Neptune/OpenSearch Experience integrating agents with CRM, service, telephony, or workflow platforms such as Salesforce or Genesys Ideal Candidate Strong software engineer with recent enterprise GenAI and agentic AI experience Enjoys turning ambiguous business use cases into reliable, governed, production-ready agents Comfortable working across cloud architecture, data integration, AI orchestration, and production operations