CoreAi Consulting

Design, develop, and deploy scalable AI/ML applications and microservices in cloud environments, focusing on data pipelines, model deployment, and system orchestration. | Over 8 years of experience in software/AI engineering, expert Python skills, extensive AWS and containerization experience, and specialized knowledge in generative AI and agentic systems. | We are seeking a highly skilled Mid–Senior 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 design—data, infrastructure, orchestration, and model integration—across 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. We are seeking a highly skilled Mid–Senior 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 design—data, infrastructure, orchestration, and model integration—across 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.