Senior Enterprise AI Platform Engineer

Jobgether; United States; On-site; USD 126,000 - 206,000; Full time

Benefits offered by this job

Medical, dental, and vision insurance

401(k) plan with company matching

Equity opportunities

Job summary

Jobgether is seeking an Enterprise AI Systems Engineer in the United States to own the enterprise AI technology stack from platform administration to governance and automation.

You will collaborate with cybersecurity, AI governance, finance, and business stakeholders to translate complex requirements into scalable, secure solutions, building MCP gateways and AI workflows across cloud platforms.

Qualifications

• 5+ years in software/cloud/platform engineering with hands-on LLM systems.
• Experience administering enterprise SaaS/AI platforms at scale, including access management, cost management, and adoption.
• Working knowledge of commercial and open-weight LLMs, including prompt engineering, evaluation, retrieval, and agentic architectures.
• Hands-on experience with MCP, MCP gateways, LLM gateways, or comparable API integration and middleware technologies.
• Strong experience with AWS and GCP architecture, including IAM, networking, secrets management, and managed AI services.
• Experience with GitHub and modern engineering practices including version control, code review, testing, CI/CD, and infrastructure as code.
• Strong Python and/or JavaScript/TypeScript skills for building integrations, automations, and internal tooling.
• Understanding of AI security and data governance fundamentals, including least privilege, data classification, DLP, and auditability.

Responsibilities

• Own end-to-end ownership of enterprise AI platforms and supporting infrastructure, ensuring security, reliability, and cost-effectiveness.
• Provision and manage enterprise AI/ SaaS platforms (Claude, Gemini, OpenRouter, Cursor, NotebookLM) including security and tenancy.
• Develop modules, prompts, projects, connectors, and documentation to improve platform functionality and adoption.
• Drive adoption across a growing user base while monitoring usage and opportunities to improve utilization.
• Track AI platform consumption and spending; support cost allocation and chargeback processes.
• Monitor availability, manage feature rollouts, troubleshoot issues, and own escalations.
• Build and operate MCP servers and gateways that securely connect AI platforms with internal systems.
• Maintain the LLM gateway for model routing, auth, rate limiting, logging, and policy enforcement.
• Evaluate models for workloads based on cost, latency, data sensitivity.
• Build agentic workflows and automations using internal APIs with guardrails for predictable behavior.
• Architect and operate AI workloads on AWS and GCP (Bedrock, Vertex AI).
• Develop production code in GitHub (Python/TypeScript) with CI/CD and IaC practices.
• Instrument the stack for cost, performance, and security telemetry and reporting.

Skills

LLM systems

Platform engineering

Stakeholder communication

AI governance

Cost optimization

Education

Bachelor's degree or equivalent

Tools

MCP gateways

LLM gateways

GitHub

CI/CD

IaC

Job description

Jobgether is seeking an Enterprise AI Systems Engineer in the United States to own the enterprise AI technology stack from platform administration to governance and automation.

You will collaborate with cybersecurity, AI governance, finance, and business stakeholders to translate complex requirements into scalable, secure solutions, building MCP gateways and AI workflows across cloud platforms.