Senior AI Platform Engineer
New
J
JobgetherAI Platform
Based in United StatesFull-TimeSenior
Salary$180,000 - $200,000 USD
Apply NowOpens the employer's application page
Job Details
- Experience
- 8+ years
- Required Skills
- KubernetesData engineeringRESTful APIsDatabricksLLM
Requirements
- 8+ years of backend engineering experience building scalable software systems.
- Hands-on experience with AI agent frameworks, LLM integrations, MCP servers, or AI-powered automation workflows.
- Strong understanding of backend development principles, APIs, integrations, and distributed systems.
- Experience working with REST APIs, OAuth 2.0, credential management, and cloud authentication patterns.
- Experience deploying and operating services using Kubernetes or similar container-based infrastructure.
- Background in data engineering, analytics platforms, or business intelligence environments.
- Familiarity with Databricks or similar data warehouse/data lake technologies is a plus.
- Ability to design secure, reliable systems that balance innovation with operational requirements.
- Comfortable working without an established playbook and adapting to evolving AI technologies and priorities.
- Strong communication skills with the ability to connect technical solutions with business objectives.
- Ability to collaborate across multiple teams and manage competing priorities effectively.
- Curiosity and practical experience using AI tools to improve workflows, productivity, and problem-solving.
Responsibilities
- Design and develop AI agents capable of completing complex multi-step workflows through reasoning, tool usage, automation, and human-in-the-loop processes.
- Build and maintain the tool and context layer that enables secure AI access to internal systems, data sources, and business applications through APIs, MCP servers, and retrieval systems.
- Develop, deploy, and improve MCP servers for external SaaS integrations and internal tools while ensuring production readiness, security, and reliability.
- Create authentication, authorization, and credential management solutions using secure identity patterns and OAuth-based integrations.
- Establish engineering standards for AI integrations, including deployment practices, monitoring, logging, access controls, and security requirements.
- Build plugins, skills, and AI workflow extensions that automate repetitive processes and improve productivity across teams.
- Own improvements to internal data platforms and analytics environments, ensuring data pipelines and structures are optimized for AI-powered use cases.
- Develop usage tracking and reporting systems to measure AI adoption, identify opportunities, and guide platform investments.
- Optimize AI platform infrastructure, including compute, storage, networking, and operational costs.
- Implement security and compliance best practices to ensure responsible, scalable, and auditable AI usage.
View Full Description & ApplyYou'll be redirected to the employer's site
