AI Engineer - AI Foundations and Platform Enablement

Vytwo; Dallas (TX); On-site; USD 110,000 - 140,000; Full time

Benefits offered by this job

Health insurance

Job summary

Vytwo in Dallas/Austin seeks an AI Engineer to design and build foundational AI platform layers, delivering secure, scalable, reusable AI use cases. You will create POCs and production-ready patterns across MCP, orchestration, security, caching, and telemetry.

The ideal candidate has 5+ years in software engineering for distributed services, hands-on with LLMs, and strong skills in Java/Python/TypeScript/Go. Join a team advancing enterprise-grade AI capabilities.

Qualifications

• 5+ years of software engineering experience building distributed services.
• Hands-on with LLM apps, AI agents, RAG, or tool-calling workflows.
• Strong programming skills in Java, Python, TypeScript, or Go.
• Experience with APIs, service integration, async processing, and distributed systems.
• Knowledge of authentication, authorization, secrets management, and secure service communication.
• Observability experience: logs, metrics, traces, dashboards.
• Experience with cloud and containerized deployments (Kubernetes).
• Strong communication and collaboration to turn ideas into POCs.

Responsibilities

• Build POCs for MCP gateways and servers exposing tools and data.
• Design an orchestration layer for models, agents, tools, workflows, retries, and failures.
• Establish caching patterns to improve latency and protect data freshness.
• Implement agentic authentication and authorization with identity propagation and least privilege.
• Create telemetry for AI workflows: traces, metrics, logs, token usage and tool calls.
• Deliver reusable APIs, reference implementations, docs and standards.
• Partner with architecture, security, product and engineering to move POCs to production.

Skills

Distributed services

LLM applications

Java

Python

TypeScript

Go

APIs

Authentication

Kubernetes

Cloud deployments

Tools

MCP gateways

MCP servers

Agent integration frameworks

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