Cloud AI Engineer

Intellectt INC

  • Boston, MA
  • Today
  • $60–$65

Highlights

This role is responsible for accelerating enterprise AI adoption by architecting and deploying scalable, secure, and cost-optimized Generative AI solutions-including advanced Retrieval-Augmented Generation (RAG) pipelines, Model Context Protocol (MCP) integrations, and autonomous AI agents. Provision and manage cloud infrastructure using Infrastructure as Code (Terraform / CloudFormation) across AWS resources (VPC, EKS, EC2, SNS/SQS, CloudWatch, Route 53, ELB) and Snowflake virtual warehouses.

Numbers & Facts

LocationBoston, MA
Salary$60–$65

Description

Role: Cloud AI Engineer

Company: Intellectt Inc

Location: Boston, MA (Onsite)

Employment Type: Contract

Interview Mode: Online interview

Job Description:

Our client is seeking an experienced Cloud AI Engineer with deep expertise across cloud architecture, data engineering, AI/ML frameworks, infrastructure automation, and cloud security. This role is responsible for accelerating enterprise AI adoption by architecting and deploying scalable, secure, and cost-optimized Generative AI solutions-including advanced Retrieval-Augmented Generation (RAG) pipelines, Model Context Protocol (MCP) integrations, and autonomous AI agents. The ideal candidate will bridge data engineering on AWS and Snowflake with modern LLM-driven application workflows, ensuring adherence to the AWS Well-Architected Framework and enterprise-grade security standards.

Responsibilities:

  • Architect, build, and deploy enterprise Retrieval-Augmented Generation (RAG) applications using vector databases, embedding models, semantic search engines, and enterprise knowledge repositories.

  • Design, develop, and integrate Model Context Protocol (MCP) servers and clients to establish secure, standardized connectivity between AI agents, LLMs, enterprise APIs, and data stores.

  • Implement robust enterprise AI security, data privacy, and governance frameworks, covering prompt injection mitigation, content filtering, AI Gateway policies, and RBAC across AI services.

  • Optimize generative AI workloads for performance and cost efficiency through model selection, token management, intelligent semantic caching, and latency reduction strategies.

  • Design, build, and maintain large-scale data engineering and analytics pipelines hosted on AWS and Snowflake.

  • Provision and manage cloud infrastructure using Infrastructure as Code (Terraform / CloudFormation) across AWS resources (VPC, EKS, EC2, SNS/SQS, CloudWatch, Route 53, ELB) and Snowflake virtual warehouses.

  • Configure and administer Snowflake environments, ensuring query optimization, storage management, role-based access controls (RBAC), and row/column-level security.

  • Manage secure private networking, routing, and endpoint connections (AWS PrivateLink) bridging AWS services, Snowflake, and Tableau Cloud/Server.

  • Build and maintain automated CI/CD deployment pipelines using GitHub Actions for infrastructure, data pipelines, and application artifacts across multi-environment setups.

  • Troubleshoot complex data platform and model serving incidents, performing root-cause analysis and implementing preventive measures to ensure high availability.

Required Skills:

  • Bachelor's degree in Computer Science, Information Technology, Mathematics, or a related discipline.

  • 10+ years of dedicated experience architecting, building, and deploying robust data and cloud solutions on AWS.

  • Demonstrated hands-on experience designing and operating cloud-native Generative AI and production RAG pipelines (vector search, embeddings, document ingestion).

  • Practical experience with Model Context Protocol (MCP), building and integrating MCP servers and client tools for agentic AI architectures.

  • Strong proficiency in Infrastructure as Code (IaC) utilizing Terraform or AWS CloudFormation.

  • Advanced proficiency in Python and complex SQL for data transformation, pipeline development, and AI integration.

  • In-depth Snowflake platform administration experience, including warehouse sizing, performance tuning, and fine-grained data governance.

  • Proven experience with foundational AWS compute and networking (VPC, EKS, EC2, PrivateLink, IAM, Security Groups).

  • Hands-on experience developing CI/CD workflows and automated release testing using GitHub Actions.

  • Practical understanding and implementation of the AWS Well-Architected Framework pillars.

  • Relevant AWS certifications (e.g., AWS Solutions Architect, AWS Machine Learning Specialty, or Data Engineer) preferred.

Pay Scale: $60 $65/hr on W2

Benefits: Employees hired into this position are eligible for the following benefits, subject to applicable plan terms and eligibility requirements:

Health Insurance: Medical, dental, and vision insurance options are available through a third-party provider. Employees are responsible for paying the full cost of their insurance premiums.

Retirement Benefits: A 401(k) retirement savings plan is available. No employer matching or other employer contributions are provided.

Paid Time Off (PTO): No PTO other than that required by applicable state and local laws.

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