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Agentic AI Engineer with Agent Core experience

Atinfo Technology IncJersey City, NJ🇺🇸United StatesPosted 10 Sept 2026

Why This Role Stands Out

Advance your career as an Agentic AI Engineer with Atinfo Technology Inc., where you'll build cutting-edge AI agents using Amazon Bedrock and AgentCore, shaping innovative solutions. This hybrid role is perfect for mid-senior engineers with a passion for prompt engineering, tool development, and secure AI, offering a dynamic environment to grow your expertise. Join a forward-thinking team and contribute to impactful projects – apply today!

Quick Overview

Seniority
Mid Senior
Work mode
Hybrid
Location
Jersey City, NJ, United States
Posted
18 hours ago
API Gateway

Job Description

Full Time role. No C2C Allowed.

Agentic AI Engineer Bedrock Agents & AgentCore Hands-on experience building and deploying AI agents using Amazon Bedrock Agents and AgentCore Runtime, including agent orchestration, multi-agent workflows, session management, and serverless deployment patterns.

Agent Tool Development Ability to design and implement agent tools (Lambda-backed, API Gateway, MCP) that enable agents to interact with backend services for data ingestion, model execution, and reporting workflows within the MMix pipeline.

Strands Agents SDK Experience with the Strands Agents framework for building custom agents with tool use, conversation management, and integration with Bedrock foundation models.

Prompt Engineering & Agent Reasoning Strong understanding of prompt design for agentic workflows system prompts, tool selection instructions, chain-of-thought reasoning, and guardrails to ensure agents follow prescribed MMix workflows (data validation model training output generation reporting).

AgentCore Identity & Security Knowledge of AgentCore Identity for agent authentication, workload identities, credential providers (OAuth2, API key), and secure access to customer data sources and downstream services within Merck's security requirements. Knowledge

Bases & RAG Experience setting up and tuning Bedrock Knowledge Bases for domain-specific retrieval, including data source ingestion, chunking strategies, embedding models, and integrating retrieved context into agent responses for marketing mix domain knowledge.

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