AWS Agentic AI Engineer

This hybrid role in Dallas, TX focuses on designing, building, and deploying autonomous and semi-autonomous AI agents on AWS. You will work with goal-driven, tool-using, multi-step systems that combine AWS AI/ML services with LLMs, while integrating enterprise systems and emphasizing production-grade safety and reliability. Responsibilities

Design and develop agentic AI systems using

Amazon Bedrock

and other foundation models, including

Claude

and

Titan . Build autonomous and semi-autonomous AI agents that perform multi-step reasoning, planning, tool usage, action execution, and human-in-the-loop collaboration. Integrate with

Amazon SageMaker

for custom model training, fine-tuning, evaluation, and experimentation. Implement

Retrieval Augmented Generation (RAG)

solutions using

Amazon OpenSearch ,

Amazon Aurora ,

DynamoDB , and vector databases such as

FAISS

or

Pinecone . Optimize inference cost, latency, scalability, and reliability across AI workloads. Implement guardrails, validation layers, and human-in-the-loop controls to support safe, reliable, and predictable AI behavior. Address hallucination mitigation, prompt injection risks, bias concerns, and model misuse scenarios. Ensure compliance with enterprise AI governance, security, and regulatory standards. Implement comprehensive logging, monitoring, observability, and audit trails for AI systems. Support production deployments, incident resolution, and root cause analysis for AI services. Continuously improve agent performance, reliability, robustness, and usability through iteration, monitoring, and feedback. Collaborate with architecture, DevOps, data engineering, security, and business teams to deliver end-to-end AI solutions. Requirements

Bachelor’s degree in

computer science, Engineering, Technology, or a related field , with

8–12 years of overall IT experience

and at least

3+ years of hands‑on experience

building agentic AI solutions using

AWS cloud‑native services . Strong expertise in core AWS services:

AWS Lambda ,

Step Functions ,

EventBridge ,

S3 ,

DynamoDB

or

Aurora ,

OpenSearch ,

Amazon Bedrock , and

Amazon SageMaker . Advanced proficiency in

Python

for building scalable AI systems and automation workflows. Proven experience leading the technical design and implementation of complex AI agent architectures and components. Hands‑on experience designing

RAG

solutions and applying model fine‑tuning techniques. Demonstrated ability to manage performance, scalability, reliability, and cost optimization of AI workloads in production environments. Proven experience conducting code reviews, leading knowledge‑sharing sessions, and making critical decisions on technologies, architectures, and frameworks. Healthcare domain experience is desirable, along with knowledge of AI safety, governance, compliance, and responsible AI practices. AWS certifications such as

Solutions Architect

or

Machine Learning Specialty

are preferred; experience with

LangChain

and

LangGraph

is a plus. Excellent communication skills with the ability to collaborate effectively with technical and non-technical stakeholders. Required Skills & Technologies

AWS, Amazon Bedrock, Amazon SageMaker, Amazon OpenSearch, Amazon Aurora, DynamoDB AWS Lambda, Step Functions, EventBridge, S3 Python Claude, Titan FAISS, Pinecone LangChain, LangGraph Experience

Minimum experience:

3 years Education:

Bachelor’s degree Location

Dallas, TX

(hybrid)

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