AI Engineer - AI Foundations and Platform Enablement

Vytwo

  • Dallas, TX
  • 12 days ago
  • $60 Per Hour
  • Full-time

Highlights

Design an orchestration layer for coordinating models, agents, tools, workflows, approvals, retries, and failures. - Build POCs for MCP gateways and retail-domain MCP servers that securely expose enterprise tools and data.

Numbers & Facts

LocationDallas, TX
Job TypeFull-time

Description

Benefits:
  • Health insurance

 
AI Engineer - AI Foundations and Platform Enablement –
Location: Dallas, TX and Austin, TX
Hire type: C2H and FTE
Salary: $60/hr / $120K on FTE


Role Summary


Design and build the foundational platform layers needed to deliver secure, scalable, reusable AI use cases. The role will develop proofs of concept and production-ready patterns across MCP, orchestration, security, caching, and telemetry.


Key Responsibilities

- Build POCs for MCP gateways and retail-domain MCP servers that securely expose enterprise tools and data.
- Design an orchestration layer for coordinating models, agents, tools, workflows, approvals, retries, and failures.
- Establish caching patterns that improve latency and cost while protecting data freshness and privacy.
- Implement agentic authentication and authorization, including identity propagation, delegated access, least privilege, and auditability.
- Create telemetry for AI workflows, including traces, metrics, logs, token usage, tool calls, latency, errors, and policy decisions.
- Deliver reusable APIs, reference implementations, documentation, and standards for application teams.
- Partner with architecture, security, product, and engineering teams to move POCs toward production.

 Must Have


- 5+ years of software engineering experience building distributed services or platforms.
- Hands-on experience with LLM applications, AI agents, RAG, or tool-calling workflows.
- Strong programming skills in Java, Python, TypeScript, or Go.
- Experience with APIs, service integration, asynchronous processing, and distributed systems.
- Practical knowledge of authentication, authorization, secrets management, and secure service communication.
- Experience with observability, including structured logging, metrics, tracing, and operational dashboards.
- Experience with cloud and containerized deployments, such as Kubernetes.
- Strong communication and collaboration skills, with the ability to turn ambiguous ideas into working POCs.

Nice to Have


- Experience with Model Context Protocol, MCP gateways, MCP servers, or similar agent integration frameworks.
- Experience building orchestration or workflow platforms with durable execution, queues, event streams, or human-in-the-loop controls. 

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