Senior Agentic AI Engineer

We are seeking a Senior Agentic AI Engineer to design, build, and optimize production-grade agentic AI solutions using large language models, advanced reasoning frameworks, and cloud-native architectures. This role will focus on building intelligent, scalable, and observable AI systems on AWS, with strong emphasis on AWS Bedrock AgentCore, multi-agent orchestration, A2A/MCP integration, RAG, NL2SQL, and end-to-end deployment of enterprise AI capabilities. This aligns with the core responsibilities and technologies listed in your draft, including Bedrock AgentCore components, A2A/MCP servers, Strands Agents, observability, LLM engineering, vector retrieval, and agent frameworks.

Key Responsibilities

• Design, build, and optimize agentic AI applications and product features using AWS Bedrock AgentCore
• Develop serverless, scalable, and production-ready AI architectures on AWS
• Implement and operate A2A and MCP servers on AWS, and integrate them with Bedrock Agents and Converse APIs
• Orchestrate multi-agent workflows and reasoning pipelines using frameworks such as Strands Agents
• Build robust observability and auditability into agent systems using CloudWatch metrics, traces, and logs
• Develop and improve NL2SQL / Text-to-SQL pipelines using LLMs and AI/ML techniques
• Design and optimize RAG pipelines using vector databases, embeddings, and structured/unstructured enterprise data
• Integrate AI systems with data connectors, APIs, and gateway services to enable seamless enterprise workflows
• Partner with product managers, data engineers, UX teams, and stakeholders to deliver measurable business impact
• Contribute to the AI roadmap, solution design, evaluation standards, and production deployment best practices

Required Skills & Experience

• 7+ years of software engineering experience, with strong hands-on work in Python and distributed/cloud-based application development
• 3+ years of experience in Generative AI / LLM application development
• Strong hands-on experience with AWS Bedrock AgentCore, especially Memory, Gateway, Runtime, Identity, Observability, or related services
• Experience building agentic workflows, multi-agent systems, or reasoning-based AI applications
• Strong understanding of LLMs, including prompt engineering, evaluation, fine-tuning concepts, and production usage patterns
• Hands-on experience with RAG architectures, vector databases, embedding models, and enterprise retrieval workflows
• Experience building NL2SQL / Text-to-SQL solutions using AI/ML or LLM-based approaches
• Hands-on experience with one or more agent frameworks such as Strands, LangGraph, LangChain Agents, Semantic Kernel, or CrewAI
• Experience integrating AI services with APIs, data connectors, and gateway-based enterprise systems
• Strong problem-solving skills with the ability to work in a fast-paced, innovation-driven environment
• Strong communication and stakeholder management skills, with the ability to explain complex AI concepts clearly

Preferred Qualifications

• Experience with AWS-native observability and monitoring for AI applications
• Exposure to enterprise AI ecosystems such as OpenAI, Anthropic, Azure AI Foundry, Copilot Studio, Google Gemini, or Microsoft 365 Copilot
• Experience working with structured and unstructured data for AI training, retrieval, and reasoning workflows
• Experience in productionizing AI solutions with governance, auditability, security, and measurable business outcomes
• Familiarity with enterprise-scale solution design and cross-functional delivery

Nice-to-Have Skills

• Experience with fine-tuning workflows or LLM adaptation strategies
• Exposure to agent governance, evaluation frameworks, and AI safety/guardrails
• Experience supporting data-driven transformation initiatives across business teams
• Prior experience in highly collaborative, research-driven, or innovation-led engineering environments

What Success Looks Like

• Build and deploy scalable agentic AI systems that are reliable, observable, and enterprise-ready
• Deliver measurable improvements in automation, reasoning, retrieval quality, and user productivity
• Establish strong engineering patterns for multi-agent architecture, RAG, and Bedrock-based AI delivery
• Serve as a key technical contributor in shaping the organization’s agentic AI strategy

My take on this rewrite

This version fixes the biggest problems in your draft:

• gives the role a stronger title than “Agentic Developer”
• separates responsibilities, required skills, and preferred skills
• removes awkward fragment-style lines from the original draft such as the incomplete responsibility phrasing
• keeps the real technical stack from your document: Bedrock AgentCore, A2A/MCP, Strands, CloudWatch, LLMs, Python, NL2SQL, vector databases, RAG, and agent frameworks

Pay: $70.00 - $80.00 per hour

Work Location: In person