CoreAi Consulting
AI & Cloud Engineer - Remote (Phoenix)
CoreAi Consulting, Phoenix, Arizona, United States, 85003
We are seeking a highly skilled MidSenior Level Engineer with strong expertise in Python, AWS cloud services, containerization, and modern AI/ML technologies. The ideal candidate has hands-on experience designing scalable data ingestion pipelines, deploying GenAI/LLM solutions, and building retrieval-augmented and agentic systems for enterprise use cases. This role involves end-to-end solution designdata, infrastructure, orchestration, and model integrationacross cloud-native environments.
Key Responsibilities Design, develop, and deploy scalable applications and microservices using
Python
and
AWS
services (Lambda, ECS/EKS, S3, DynamoDB, API Gateway, Bedrock, CloudFormation, etc.). Build and maintain
containerized
workloads using
Docker , GitHub workflows, and CI/CD automation. Develop robust
data ingestion and processing pipelines
integrating structured/unstructured data sources. Implement GenAI solutions using
LLMs, embeddings, vector databases (Pinecone, FAISS, Redis, etc.) , and
RAG
architectures. Build and manage
knowledge bases , embedding pipelines, and context-retrieval systems optimized for real-world performance. Design and orchestrate
agentic workflows
using modern
agentic frameworks
and multi-agent patterns for automation and decision-making. Work with
AWS Bedrock
to integrate foundation models, manage guardrails, tune prompts, and optimize model performance. Implement secure, scalable infrastructure using
CloudFormation , IAM, VPC, and AWS networking best practices. Collaborate with cross-functional teams (data, product, engineering) to translate requirements into technical designs. Monitor, troubleshoot, and optimize production AI/ML workloads, including inference performance, latency, cost, and reliability. Maintain strong code quality standards through GitHub version control, documentation, and automated testing.
Required Skills & Experience 8+ years of professional experience in software engineering, cloud engineering, or ML/AI development. Expert-level programming skills in
Python
(FastAPI, Flask, Async frameworks preferred). Deep experience with
AWS services , including serverless and container architectures. Hands-on experience with
Docker , CI/CD, and IaC tools like
CloudFormation
or CDK. Proven experience building
RAG pipelines , vector store integrations, and embedding workflows. Strong understanding of
LLMs , prompt engineering, model evaluation, and generative AI development. Experience with
agentic orchestration
(LangChain, LlamaIndex, custom agent frameworks, or AWS Agents). Experience integrating with
AWS Bedrock
or similar foundation model platforms. Solid understanding of distributed systems, API development, security, and cloud-native patterns. Strong problem-solving abilities and the ability to work independently in fast-paced environments.
Key Responsibilities Design, develop, and deploy scalable applications and microservices using
Python
and
AWS
services (Lambda, ECS/EKS, S3, DynamoDB, API Gateway, Bedrock, CloudFormation, etc.). Build and maintain
containerized
workloads using
Docker , GitHub workflows, and CI/CD automation. Develop robust
data ingestion and processing pipelines
integrating structured/unstructured data sources. Implement GenAI solutions using
LLMs, embeddings, vector databases (Pinecone, FAISS, Redis, etc.) , and
RAG
architectures. Build and manage
knowledge bases , embedding pipelines, and context-retrieval systems optimized for real-world performance. Design and orchestrate
agentic workflows
using modern
agentic frameworks
and multi-agent patterns for automation and decision-making. Work with
AWS Bedrock
to integrate foundation models, manage guardrails, tune prompts, and optimize model performance. Implement secure, scalable infrastructure using
CloudFormation , IAM, VPC, and AWS networking best practices. Collaborate with cross-functional teams (data, product, engineering) to translate requirements into technical designs. Monitor, troubleshoot, and optimize production AI/ML workloads, including inference performance, latency, cost, and reliability. Maintain strong code quality standards through GitHub version control, documentation, and automated testing.
Required Skills & Experience 8+ years of professional experience in software engineering, cloud engineering, or ML/AI development. Expert-level programming skills in
Python
(FastAPI, Flask, Async frameworks preferred). Deep experience with
AWS services , including serverless and container architectures. Hands-on experience with
Docker , CI/CD, and IaC tools like
CloudFormation
or CDK. Proven experience building
RAG pipelines , vector store integrations, and embedding workflows. Strong understanding of
LLMs , prompt engineering, model evaluation, and generative AI development. Experience with
agentic orchestration
(LangChain, LlamaIndex, custom agent frameworks, or AWS Agents). Experience integrating with
AWS Bedrock
or similar foundation model platforms. Solid understanding of distributed systems, API development, security, and cloud-native patterns. Strong problem-solving abilities and the ability to work independently in fast-paced environments.