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AWS AI Architect

Hybrid in Gainesville, FL, US • Posted 14 hours ago • Updated 14 hours ago

Contract W2

12 Months

No Travel Required

Able to Sponsor

On-site

$65 - $70/hr

Fitment

Dice Job Match Score™

🛠️ Calibrating flux capacitors...

Job Details

Skills

Machine Learning Operations (ML Ops)
Document Processing
Generative Artificial Intelligence (AI)
Continuous Integration
Database
Decision-making
Amazon Web Services
Artificial Intelligence
Continuous Delivery
Docker
Prompt Engineering
Scalability
Semantic Search
Software Engineering
Machine Learning (ML)
Microservices
Orchestration
Python
Evaluation
Kubernetes
LangChain
LlamaIndex
Mentorship
Training
Amazon DynamoDB
Amazon S3
Amazon SageMaker
Cloud Security
Git
API
Vector Databases
Virtual Private Cloud
Workflow

Machine Learning Operations (ML Ops)
Document Processing
Generative Artificial Intelligence (AI)
Continuous Integration
Database
Decision-making
Amazon Web Services
Artificial Intelligence
Continuous Delivery
Docker
Prompt Engineering
Scalability
Semantic Search
Software Engineering
Machine Learning (ML)
Microservices
Orchestration
Python
Evaluation
Kubernetes
LangChain
LlamaIndex
Mentorship
Training
Amazon DynamoDB
Amazon S3
Amazon SageMaker
Cloud Security
Git
API
Vector Databases
Virtual Private Cloud
Workflow

Summary

Key Responsibilities

Design and implement AI/ML solutions on AWS for enterprise-scale applications.
Build and deploy Generative AI, LLM, RAG, and AI Agent solutions.
Architect AI platforms using Amazon Bedrock, SageMaker, Lambda, ECS/EKS, API Gateway, S3, DynamoDB, and OpenSearch.
Develop scalable Python-based AI/ML services, REST APIs, and microservices.
Implement RAG pipelines using embeddings, vector databases, document processing, and semantic search.
Build AI agents and agentic workflows with tool calling, orchestration, planning, and autonomous decision-making.
Integrate LLMs with enterprise applications, databases, APIs, and business workflows.
Design MLOps/LLMOps pipelines for model training, evaluation, deployment, monitoring, and governance.
Implement AWS security using IAM, KMS, Secrets Manager, VPC, CloudTrail, GuardDuty, and related services.
Optimize AI workloads for performance, scalability, reliability, and cost.
Lead technical discussions with architects, engineering teams, product teams, and business stakeholders.
Mentor senior engineers and establish AI engineering best practices.

Required Skills

10+ years of software engineering / AI / ML experience.
Strong Python development experience.
Hands-on AWS experience with:
- Amazon Bedrock
- Amazon SageMaker
- AWS Lambda
- ECS / EKS
- S3
- DynamoDB
- OpenSearch
- API Gateway
- CloudWatch
- IAM
Strong experience with Generative AI and LLMs.
Experience with RAG architecture, embeddings, vector databases, prompt engineering, and LLM evaluation.
Experience with LangChain, LlamaIndex, or similar AI frameworks.
Knowledge of OpenAI, Anthropic Claude, Llama, or other foundation models.
Experience developing REST APIs and microservices.
Strong knowledge of Docker, Kubernetes, CI/CD, Git, and Infrastructure as Code.
Experience with ML pipelines, MLOps, model monitoring, and production deployment.
Strong understanding of AWS architecture and cloud security.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: 91138713
Position Id: 9055331
Posted 14 hours ago

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