Artificial Intelligence Engineer

We are seeking an experienced cloud AI engineer who possesses deep expertise in cloud technologies, data engineering, AI/ML frameworks, infrastructure automation, and cloud security, along with a strong understanding of emerging AI technologies and industry best practices. The Cloud AI Engineer will play a critical role in accelerating AI adoption, improving operational efficiency, optimizing cloud investments, and enabling innovative, enterprise-scale AI solutions that drive business value.

• Proven experience architecting and implementing retrieval-augmented generation (RAG) solutions using vector databases, embedding models, semantic search, and enterprise knowledge repositories to deliver accurate, context-aware, and scalable generative AI applications.
• Strong knowledge of enterprise AI security practices, including identity and access management, data privacy, prompt injection mitigation, content filtering, responsible AI principles, and governance controls across AI Gateway, MCP, RAG, and agentic AI implementations.
• Experience in optimizing AI workloads through intelligent model selection, token usage management, caching, efficient retrieval strategies, latency reduction, and cloud resource optimization while maintaining application performance and reliability.
• Ability to integrate LLM-powered applications and AI agents with enterprise systems, cloud services, databases, and APIs using secure integration patterns, MCP-based tool connectivity, and event-driven architectures
• Implement technical efforts to design, build, and deploy AWS-hosted data solutions, including large-scale data processing pipelines, computationally intensive statistical modeling, and advanced analytics.
• Participate in all aspects of the software development lifecycle (SDLC) for AWS solutions, including planning, requirements gathering, development, automated testing, and quality assurance.
• Expertly troubleshoot incidents, identify root causes, fix and document complex issues, and implement preventive measures to ensure system stability.
• Educate cross-functional teams on the implementation of new cloud-based data initiatives, providing associated training and technical documentation when necessary.
• Demonstrate exceptional problem-solving skills, with a proven ability to see, predict, and resolve data bottlenecks or system issues before they impact business productivity.
• Utilize Terraform to provision, manage, and orchestrate AWS infrastructure and Snowflake resources efficiently.
• Oversee and implement upgrades, performance tuning, and access controls within Tableau Server/Cloud, ensuring seamless integration with AWS services and optimal dashboard performance.
• Configure and manage virtual compute resources ( AWS EC2 and Snowflake Virtual Warehouses), focusing on optimal configuration, sizing, elasticity, auto-scaling, and cost control.
• Implement and maintain rigorous security configurations, including AWS IAM, Snowflake Role-Based Access Control (RBAC), network policies, and Row/Column-level security to protect sensitive data.
• Perform data platform administrative functions across AWS and Snowflake, ensuring smooth operations, query optimization, storage management, and compliance with best practices.
• Configure and manage load balancing strategies and failover routing ( AWS ELB/Route 53) to ensure high availability and fault tolerance across data applications and BI endpoints.
• Design and manage AWS VPC networks, security groups, and private endpoints ( AWS PrivateLink) to ensure secure, efficient, and private connectivity between AWS, Snowflake, and Tableau.

• 10 or more years of experience in architecting, designing, developing, and implementing robust data and cloud solutions on the AWS platform.
• Demonstrated expertise in building Retrieval-Augmented Generation (RAG) solutions using vector databases, embedding models, semantic search, document processing, and enterprise knowledge repositories.
• Strong hands-on experience designing, developing, and deploying cloud-native AI/ML and Generative AI solutions
• Hands-on experience with Model Context Protocol (MCP), including developing and integrating MCP servers and clients to securely connect AI agents and LLM applications with enterprise systems, APIs, and data sources.
• Deep technical experience provisioning and managing foundational AWS components, including Amazon Elastic Kubernetes Service (EKS), VPC, Amazon SNS/SQS, Amazon CloudWatch, AWS CloudFormation, and Amazon EC2.
• Proven track record executed in cloud migration strategies, including On-Premises to AWS and cross-cloud (Cloud Provider to AWS) migrations.
• Advanced proficiency with Infrastructure as Code tools, specifically Terraform or AWS CloudFormation, to automate infrastructure deployment.
• Thorough understanding and practical application of the AWS Well-Architected Framework pillars (Operational Excellence, Security, Reliability, Performance Efficiency, Cost Optimization, and Sustainability).
• Hands-on experience with GitHub and GitHub Actions, including developing, configuring, and maintaining automated CI/CD workflows for building, testing, and deploying cloud infrastructure and data pipelines.
• Proficiency in Git-based version control, branching strategies, pull requests, code reviews, and integrating GitHub Actions with AWS, Terraform, and Snowflake for secure, automated deployments across multiple environments.
• Demonstrated hands-on experience in Snowflake administration, including performance tuning, security, and access management; strong proficiency in Python and advanced SQL;
• Specialized experience across multiple data domains, including Database Architecture, ETL/ELT pipeline development, Business Intelligence (BI), Power BI and Tableau Administration

Preferred skills and qualifications

• Bachelor’s degree (or equivalent) in computer science, information technology, or mathematics

AWS certification

• While an hourly range is posted for this position, an eventual hourly rate is determined by a comprehensive salary analysis which considers multiple factors including but not limited to: job-related knowledge, skills and qualifications, education and experience as compared to others in the organization doing substantially similar work, if applicable, and market and business considerations. Benefits offered include medical, dental and vision benefits; dependent care flexible spending account; 401(k) plan; voluntary life/short term disability/whole life/term life/accident and critical illness coverage; employee assistance program; sick leave in accordance with regulation. Benefits may be subject to generally applicable eligibility, waiting period, contribution, and other requirements and conditions. Benefits offered are in accordance with applicable federal, state, and local laws and subject to change at TCM’s discretion.