AI Engineer - AI Foundations and Platform Enablement

Vytwo Technologies Inc.; Prosper (TX); On-site; USD 108,000 - 132,000; Full time

Benefits offered by this job

Health insurance

Job summary

Vytwo Technologies Inc. is hiring an AI Engineer to design and build foundational AI platform layers for secure, scalable use cases. You will develop proofs of concept and production-ready patterns across MCP, orchestration, security, caching, and telemetry.

The role requires hands-on work with LLM apps, AI agents, RAG, and tool-calling workflows, plus strong skills in Java/Python/TypeScript/Go and Kubernetes-based deployments.

Qualifications

• 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.

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

RAG

Tool-calling workflows

Java

Python

TypeScript

Go

APIs

Asynchronous processing

Security basics

Observability

Kubernetes

Cloud deployments

Tools

Kubernetes

Job 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.