Back to search
Benefits:
- Health insurance
Â
AI Engineer - AI Foundations and Platform Enablement –
Location: Dallas, TX and Austin, TX
Hire type: C2H and FTE
Salary: $60/hr / $120K on FTE
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
- 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
- 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.Â
- Experience building orchestration or workflow platforms with durable execution, queues, event streams, or human-in-the-loop controls.Â
Learn more about this Employer on their Career Site
