Senior AI Engineer

1. AI Agent Development and Engineering 

• Design, develop, and deploy AI Agents using cloud-native and open-source agent frameworks. 

• Build agentic workflows using Azure AI Foundry Agent Service, AWS Bedrock AgentCore, LangGraph, Strands Agents SDK, Semantic Kernel, and AutoGen. 

• Implement tool/function calling, memory, state management, checkpointing, multi-agent orchestration, and agent-to-agent workflows. 

• Integrate enterprise tools, APIs, databases, knowledge bases, and automation systems using MCP Model Context Protocol and custom connectors. 

• Design and implement RAG Retrieval-Augmented Generation solutions using vector stores, knowledge bases, and search services. 

• Develop guardrails, prompt evaluation, content safety controls, tracing, and observability for AI Agent solutions. 

• Optimize AI Agent performance, cost, latency, reliability, and user experience. 

2. Custom Application Development 

• Develop scalable web applications and internal tools to enable AI, automation, and cloud service capabilities. 

• Build frontend applications using React, TypeScript, REST API integration, GraphQL integration, and secure authentication flows. 

• Implement authentication and authorization using OAuth2, OIDC, and MSAL. 

• Develop backend services using C#/.NET, Python FastAPI, or Node.js. 

• Design and build microservices, APIs, event-driven services, and cloud-native integrations. 

• Work with relational and NoSQL databases including SQL, Cosmos DB, and DynamoDB. 

• Integrate messaging and event-driven platforms such as Azure Service Bus, AWS SQS, and AWS SNS. 

• Implement backend testing, API testing, unit testing, integration testing, and code quality practices. 

• Ensure application solutions are secure, scalable, maintainable, and aligned with enterprise architecture standards. 

3. Cloud AI Services Support 

• Deploy, manage, and support AI/ML workloads across Azure, AWS, and GCP. 

• Support Azure AI Foundry, Azure OpenAI, Azure AI Search, model deployments, evaluation, tracing, tool/function calling, and content safety controls. 

• Support AWS Bedrock, Bedrock Studio, Amazon Q Business, Bedrock Knowledge Bases, Guardrails, and Bedrock AgentCore. 

• Support GCP Vertex AI, Vertex AI Search, and Gemini Models. 

• Ensure secure and compliant deployment of AI services, APIs, agents, and applications. 

4. Cloud Operations and Optimization 

• Resolve complex cloud infrastructure and AI platform issues across Azure, AWS, and GCP. 

• Perform root cause analysis for incidents related to AI services, agents, applications, APIs, integrations, and cloud platforms. 

• Manage and optimize cloud resources including compute, storage, networking, databases, containers, and AI services. 

• Implement and monitor backup, disaster recovery, high availability, resiliency, and operational readiness. 

• Identify automation opportunities to reduce manual effort and improve operational efficiency. 

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