Agentic AI Engineer – Generative AI & Agentic Systems

Cloud Analytics Technologies, LLC; Chicago (IL); In loco; USD 88.000 - 118.000; Tempo pieno

Descrizione del lavoro

Cloud Analytics Technologies, LLC is seeking an Agentic AI Engineer to design and implement autonomous, multi-agent AI systems in a government-focused Chicago setting. The role requires hands-on work with LLMs, RAG, and enterprise-scale AI deployments.

You will build workflows, tool-calling architectures, and RESTful APIs while ensuring safety, compliance, and scalable, IaC-driven infrastructure on AWS. Collaboration with product, data, and engineering teams is essential.

Competenze

• Bachelor's or Master's degree in Computer Science, Engineering, Artificial Intelligence, Data Science, or a related field.
• 7+ years of software engineering experience, including significant experience building AI/ML solutions.
• 4+ years of hands-on experience with Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) architectures.
• 2+ years of experience designing and implementing Agentic AI or multi-agent systems.
• Experience deploying production-scale AI applications in cloud environments.

Mansioni

• Design and develop autonomous and multi-agent AI systems using AWS AgentCore capabilities.
• Build and optimize agent workflows using LangGraph and LangChain.
• Implement planning, reasoning, tool usage, and memory management capabilities within AI agents.
• Design agent-to-agent and agent-to-system interaction patterns.
• Experience of MCP (Model Context Protocol) and tool-calling architectures.
• Build enterprise-scale Retrieval-Augmented Generation (RAG) solutions using AWS Bedrock foundation models and embedding models.
• Design vectorization, indexing, retrieval, re-ranking, and grounding strategies.
• Develop prompt engineering frameworks and evaluation methodologies for GenAI applications.
• Implement conversational AI, knowledge assistants, copilots, and AI-powered automation solutions.
• Integrate Bedrock Guardrails to ensure safety, compliance, and responsible AI practices.
• Design and develop RESTful APIs to expose AI capabilities to enterprise applications.
• Integrate AI agents with business applications, enterprise workflows, databases, and external systems.
• Develop intuitive front-end experiences using React and modern UI frameworks.
• Build scalable and reusable AI services and microservices.
• Deploy and manage AI solutions on AWS using Infrastructure as Code (IaC) principles.
• Develop and maintain infrastructure using Terraform.
• Implement CI/CD pipelines using GitLab.
• Define best practices, standards, and architectural patterns for GenAI and Agentic AI implementations.
• Collaborate with product owners, architects, data engineers, and business stakeholders.
• Ensure AI solutions adhere to security, governance, compliance, and responsible AI requirements.

Formazione

Bachelor's or Master's degree in Computer Science, Engineering, Artificial Intelligence, Data Science, or a related field

Descrizione del lavoro

Agentic AI Engineer – Generative AI & Agentic Systems

Location:

Chicago, IL

Duration:

9Months+ Extension

Domain Exposure:

Government

Client:

To Be Discussed Later

Employment Type:

W-2, 1099, C2C

Work Authorization:

US Citizen, Green Card, H-1B, OPT-EAD, CPT, Other

Job Title:Agentic AI Engineer – Generative AI & Agentic Systems

Location: Chicago, IL

Duration: 9 Months + Extension

Bill Rate: $75/hour (C2C)

Job Type: W-2, 1099, C2C

Client: To Be Discussed Later

Work Authorization: US Citizen, Green Card, OPT-EAD, CPT, H-1B, H4-EAD, Other

Key Responsibilities

• Design and develop autonomous and multi-agent AI systems using AWS AgentCore capabilities
• Build and optimize agent workflows using LangGraph and LangChain.
• Implement planning, reasoning, tool usage, and memory management capabilities within AI agents.
• Design agent-to-agent and agent-to-system interaction patterns.
• Experience of MCP (Model Context Protocol) and tool-calling architectures.
• Build enterprise-scale Retrieval-Augmented Generation (RAG) solutions using AWS Bedrock foundation models and embedding models.
• Design vectorization, indexing, retrieval, re-ranking, and grounding strategies.
• Develop prompt engineering frameworks and evaluation methodologies for GenAI applications.
• Implement conversational AI, knowledge assistants, copilots, and AI-powered automation solutions.
• Integrate Bedrock Guardrails to ensure safety, compliance, and responsible AI practices.
• Design and develop RESTful APIs to expose AI capabilities to enterprise applications.
• Integrate AI agents with business applications, enterprise workflows, databases, and external systems.
• Develop intuitive front-end experiences using React and modern UI frameworks.
• Build scalable and reusable AI services and microservices.
• Deploy and manage AI solutions on AWS using Infrastructure as Code (IaC) principles.
• Develop and maintain infrastructure using Terraform.
• Implement CI/CD pipelines using GitLab.
• Define best practices, standards, and architectural patterns for GenAI and Agentic AI implementations.
• Collaborate with product owners, architects, data engineers, and business stakeholders.
• Ensure AI solutions adhere to security, governance, compliance, and responsible AI requirements.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, Artificial Intelligence, Data Science, or a related field.
• 7+ years of software engineering experience, including significant experience building AI/ML solutions.
• 4+ years of hands-on experience with Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) architectures.
• 2+ years of experience designing and implementing Agentic AI or multi-agent systems.
• Experience deploying production-scale AI applications in cloud environments.

Preferred Qualifications

• Experience building enterprise AI copilots and conversational assistants.
• Experience with advanced orchestration workflows using LangGraph.
• Experience with AI agent evaluation, testing, and benchmarking frameworks.
• Experience with knowledge graph integrations and graph-based reasoning.
• Experience implementing Human-in-the-Loop (HITL) workflows.

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.