AI Engineer - AI Foundations and Platform Enablement

Worky; Prosper (TX); On-site; USD 110,000 - 160,000; Full time

Benefits offered by this job

Health insurance

Job summary

Worky is seeking an AI Engineer to architect foundational AI platform layers, deliver secure and scalable use cases, and build production-ready patterns across orchestration, security, caching, and telemetry.

The role emphasizes POC development, APIs, and collaboration with architecture, security, product, and engineering teams to transition to production in a dynamic Dallas/Austin environment.

Qualifications

• 5+ years of distributed software engineering experience.
• Hands-on experience with LLMs, 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.

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.

Skills

Distributed systems

LLM applications / AI agents

Programming (Java, Python, TypeScript,

Tools

Kubernetes

Job description

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.

Benefits

• Health insurance