AI engineer

Cloudious LLC; Dallas (TX); Hybrid; USD 140,000 - 200,000; Full time

Job summary

Cloudious LLC seeks an AI Engineer to design foundational AI platform layers across Dallas and Austin. You will build secure, scalable patterns for MCP gateways, orchestration, caching, and telemetry while enabling production-ready POCs.

You will partner with security, architecture, product, and engineering teams to mature these capabilities toward production deployment and enterprise adoption.

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.

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 authorisation, 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

LLM applications

AI agents

RAG

tool-calling workflows

Java

Python

TypeScript

Go

Tools

Kubernetes

Redis

OAuth 2.0 / OpenID Connect

Job description

Job Role: AI Engineer - AI Foundations and Platform Enablement

Location: Dallas, TX & Austin, TX

Domain Experience: Banking & Finance

Duration: C2H & Full-Time

JOB DESCRIPTION

• 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 authorisation, 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.
• Experience with Redis or other distributed caching technologies.
• Experience with Open Telemetry and AI observability or evaluation platforms.
• Knowledge of OAuth 2.0, OpenID Connect, workload identity, token exchange, delegated authorization, or policy engines such as OPA.
• Experience in financial services, retail investing, brokerage, or another regulated industry.
• Familiarity with responsible AI, data privacy, model governance, vector databases, embeddings, and retrieval systems.
• Experience with CI/CD, infrastructure as code, automated testing, and performance testing.

EXPECTED OUTCOMES

• Working POCs for an MCP gateway, retail MCP server, and orchestration layer.
• Reusable patterns for secure agent access, caching, and AI telemetry.
• A practical roadmap for hardening foundational capabilities for production adoption.