Senior AI Engineer

We are looking for an AI Engineer that has experience in building support agents coming from a Fullstack Software Engineering background.

Senior Agentic AI Software Engineer

Location:
Houston, TX — On-site 4 days per week

As a Senior AI Engineer, you will:

AI Agent & Agentic Systems Development

• Design, build, and deploy production-grade AI agents capable of executing complex, multi-step workflows.
• Develop agentic systems that can reason over structured and unstructured data, select and invoke tools, interact with APIs and enterprise systems, and take actions on behalf of users.
• Build intelligent support agents that can understand user intent, retrieve relevant information, maintain context, resolve requests, and elevate to human operators when required.
• Design agent architectures including orchestration, planning, tool routing, state management, memory, and context management.
• Develop multi-step and multi-agent workflows that combine LLMs, business logic, APIs, RAG, structured data, and external tools.
• Build secure mechanisms for agents to interact with enterprise applications, databases, internal systems, and third-party services.
• Implement guardrails, fallback mechanisms, permissions, and human-in-the-loop workflows for reliable production deployment.
• Develop RAG systems that allow agents to retrieve and reason over enterprise knowledge and operational data.
• Build retrieval, context, and memory pipelines to support agent performance and personalization.
• Design prompting and context-engineering strategies for complex agentic workflows.
• Integrate and orchestrate LLMs from providers such as OpenAI, Anthropic, or Google.
• Evaluate models, agent architectures, retrieval strategies, and tool-use approaches based on accuracy, latency, cost, reliability, and task completion.
• Develop automated evaluation frameworks and monitoring to measure agent quality and identify regressions.
• Stay current with emerging agent frameworks, protocols, and architectures including Lang Graph, Lang Chain, Llama Index, MCP, and similar technologies.

Software Engineering & Full-Stack Development

• Build the production software infrastructure required to support AI agents and intelligent applications.
• Develop scalable backend services, APIs, orchestration layers, and integrations using Python and frameworks such as FastAPI, Flask, or Django.
• Build user-facing applications that allow users to interact with AI agents, workflows, and intelligent systems.
• Develop frontend experiences using React, Angular, Next.js, or similar modern frameworks.
• Design and implement RESTful APIs and services that connect AI agents to enterprise applications and data sources.
• Own features end-to-end across backend services, AI orchestration, data integrations, and frontend experiences.
• Apply strong software engineering principles around architecture, modularity, testing, security, and maintainability.

Data & Agent Infrastructure

• Build and maintain data ingestion and transformation pipelines that support AI applications and agentic workflows.
• Develop data pipelines supporting RAG, agent memory, context, retrieval, and personalization.
• Integrate AI applications with data platforms including Databricks and Lakehouse architectures.
• Connect agents to databases, APIs, ML model endpoints, enterprise applications, and external tools.
• Ensure data quality, security, reliability, and performance across AI and application pipelines.
• Deploy and operate AI agents and supporting applications in production cloud environments.
• Implement CI/CD, automated testing, observability, logging, and monitoring across AI and software systems.
• Monitor agent behavior, latency, cost, reliability, and task completion in production.
• Build mechanisms to identify, diagnose, and recover from agent and system failures.
• Contribute to infrastructure-as-code and cloud-native deployment practices.
• Ensure AI systems meet enterprise requirements for security, scalability, reliability, and governance.

AI-Assisted Software Engineering

• Use AI coding tools such as Claude Code, Codex, and Augment Code as part of the day-to-day development workflow.
• Apply AI-assisted development to accelerate delivery while maintaining engineering standards around architecture, testing, security, and code quality.
• Experiment with emerging AI developer tools and agent frameworks and help establish best practices across the engineering team.

What We Need From You

• Bachelor's degree in Computer Science, Software Engineering, or a related technical field.
• 8+ years of professional…