Openkyber - Fullstack AI Engineering Manager

AI Engineer is needed in Alaska, United States.

Client: Openkyber

Location: Alaska

Contract: Temporary

Job Description

Company: Kellton Tech

Kellton Tech is a full-service software development company specializing in end-to-end IT solutions, strategic technology consulting, and product development services across various domains, including Web, SMAC (Social, Mobile, Analytics, Cloud), ERP-BPM, and IoT. We are currently seeking talented resources for one of our listed clients.

Role: Lead Full Stack Engineer

Location: Remote

Type: Long term temporary

Requirements

About You:

• 7+ years of experience designing, building, and operating scalable, cloud-native applications, data pipelines, and analytics platforms in high-availability environments.
• 3+ years of experience developing modern front-end applications using TypeScript and React, focusing on analytics dashboards and data-driven interfaces.
• Strong hands-on experience with backend technologies such as Node.js (preferably with TypeScript) and Python, building APIs, event-driven services, and data processing components for real-time analytics.
• Experience designing and maintaining reliable, scalable data ingestion, transformation, and orchestration pipelines.
• Expertise in developing responsive, secure, and high-performance user interfaces using TypeScript, JavaScript, HTML, and CSS.
• Experience with role-based access control (RBAC) and secure access patterns to ensure data governance and protection of sensitive information.
• Experience with asynchronous programming, event-driven architectures, and telemetry/event-streaming patterns.
• Hands-on experience with real-time data monitoring and analytics platforms such as Grafana and InfluxDB.
• Strong experience with cloud-based data stores and query engines such as Amazon Redshift, Athena, DynamoDB, and S3-based data lakes.
• Deep expertise in data modeling and transformation within AWS, using services such as Glue, Redshift, Athena, EMR, Lambda, and S3.
• Experience implementing Machine Learning (ML) and Artificial Intelligence (AI) solutions in analytics platforms.
• Familiarity with ML lifecycle practices and model deployment using platforms such as SageMaker Studio.
• Deep knowledge of AWS services including Lambda, SNS, SQS, S3, Step Functions, IAM, KMS, and CloudWatch.
• Experience in provisioning and managing cloud infrastructure using Infrastructure as Code tools such as AWS CDK, CloudFormation, Terraform, and AWS CLI.
• Strong focus on scalability, data integrity, reliability, and operational readiness.
• Proven ability to mentor engineers and promote engineering excellence.
• Strong analytical thinking, structured problem-solving, and effective communication skills.

Nice to Have

• Exposure to building or operating analytics capabilities within a SaaS platform environment, including multi-tenant architecture considerations.
• Familiarity with cell-based architecture patterns that support isolation, fault containment, horizontal scalability, and resilience.
• Experience designing systems that support tenant-level data isolation and secure access controls.
• Understanding of platform-level observability and operational strategies in distributed, cell-based systems.