AI Platform Engineer
About the role
As an AI Platform Engineer, you will own the full lifecycle of customer AI agents—from initial deployment and API integrations to ongoing performance optimization, security, and observability. This is a high-ownership, highly technical builder/operator role. You will bridge software engineering, cloud infrastructure, and production AI to turn ambiguous customer requirements into reliable, production-grade solutions. You will be responsible for scaling agent orchestration, maintaining infrastructure security, minimizing LLM compute/token costs, and ensuring peak platform uptime.
What you'll do
- AI Agent Deployment & Operations
- Deploy, operate, and maintain customer-specific AI environments across AWS infrastructure.
- Safe rollout of system updates and feature releases across live production deployments.
- Enforce Infrastructure as Code (IaC) practices to guarantee secure, repeatable, and scalable environments.
- Monitor overall platform health, ensuring high availability, system resilience, and reliability.
- Core Platform Engineering & Orchestration
- Architect and enhance the core AI platform that powers multi-agent workflows and orchestration.
- Improve platform observability, tracing, metrics collection, and diagnostic tooling.
- Drive long-term platform architecture, system scalability, and technical standards.
- System Integrations
- Design and build secure API integrations with third-party customer platforms (CRMs, email providers, scheduling platforms, project management systems, and custom line-of-business apps).
- Develop maintainable API wrappers, service connectors, and MCP servers for AI agent access.
- Handle complex integration challenges, including authentication flows, webhooks, rate limiting, pagination, and data synchronization.
- Data Engineering & Serverless Architecture
- Build serverless ETL pipelines and reporting infrastructure using AWS serverless tools.
- Design robust data warehousing patterns to supply AI agents with accurate operational data.
- Deliver business intelligence tools and telemetry that surface actionable operational insights.
- Security, Compliance & Credential Management
- Implement strict least-privilege access controls and secure credential/secret management for customer agents.
- Establish robust authentication/authorization workflows and safeguards against security risks (e.g., prompt injection).
- Ensure complete data isolation and protection across customer environments.
- Performance & Cost Optimization
- Optimize AI agent speed, output accuracy, and compute/token efficiency.
- Fine-tune model selection, context management, and inference routines to reduce operational costs.
- Establish cost-attribution tracking across individual customer deployments.
Requirements
- Experience: 4+ years of professional software engineering experience with demonstrated production ownership.
- Core Languages: Strong proficiency in TypeScript, Node.js, and Python.
- Data: Advanced SQL skills with experience building production-grade data pipelines and storage models.
- Cloud & IaC: Hands-on experience with AWS core services (Lambda, S3, IAM, EC2) and Terraform (or equivalent IaC tools).
- Integrations: Deep understanding of REST APIs, webhooks, OAuth/authentication flows, rate limiting, pagination, and data validation.
- AI/LLMs: Proven experience building and supporting production-level AI applications beyond basic wrapper or chatbot implementations.
- Communication: Exceptional written and verbal English communication skills, with the ability to interface with customer stakeholders and translate ambiguous requirements into technical specifications.
About Somehere
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