Agentic AI Software Engineer

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Houston / $150000 - $180000 annum

INFO

Salary

SALARY:

$150000 - $180000

Location

LOCATION

Houston

Job Type
JOB TYPE

Permanent

Agentic AI Software Engineer

$150,000-$180,000 + 15% bonus

4 days/week onsite

Overview

We are seeking an experienced software engineer to design, build, and deploy intelligent AI-driven applications and autonomous workflows in an enterprise environment. This role combines AI engineering, full-stack development, data integration, and cloud-native application delivery. The ideal candidate will have experience developing production-ready software and AI-powered solutions that leverage large language models, retrieval systems, enterprise data sources, and external tools.
The position requires ownership across the entire solution lifecycle, from backend architecture and AI orchestration to user-facing experiences, with a strong focus on reliability, security, scalability, and business impact.

Key Responsibilities

AI Agent & Intelligent Workflow Development

  • Design and develop AI agents capable of reasoning through complex business processes and executing tasks through integrations with tools, APIs, and enterprise systems.
  • Build conversational and support-oriented AI solutions that understand user intent, maintain context, and resolve or route requests appropriately.
  • Create intelligent workflows that combine language models, retrieval mechanisms, business rules, structured data, and external services.
  • Develop secure integrations connecting AI systems to databases, applications, knowledge repositories, and enterprise platforms.
  • Implement memory, context-management, and personalization capabilities for AI-driven experiences.
  • Establish guardrails, human-review processes, monitoring, and fallback strategies to ensure dependable production performance.
  • Measure and optimise solution quality, accuracy, latency, cost, tool usage, and task completion outcomes.

Full-Stack Application Development

  • Build modern user experiences that enable interaction with AI-powered applications and workflows.
  • Develop frontend solutions using contemporary web frameworks.
  • Design and implement backend services, APIs, and orchestration layers using Python-based technologies.
  • Transform advanced AI capabilities into intuitive, business-focused user experiences.
  • Own end-to-end feature delivery from architecture through deployment and maintenance.
  • Ensure applications are scalable, secure, maintainable, and enterprise-ready.

Data, Retrieval & Platform Engineering

  • Build and maintain data ingestion processes, integrations, and transformation pipelines.
  • Develop retrieval-augmented solutions that leverage structured and unstructured enterprise data.
  • Design systems supporting context management, memory, personalization, and information retrieval.
  • Integrate AI applications with databases, APIs, workflow platforms, and machine learning services.
  • Maintain high standards for data quality, reliability, security, and operational performance.

AI & Language Model Engineering

  • Integrate and orchestrate large language models for production use cases.
  • Design prompting, retrieval, tool-calling, and agent orchestration strategies.
  • Develop capabilities such as conversational assistants, intelligent search, document processing, workflow automation, and knowledge discovery.
  • Evaluate models, frameworks, architectures, and AI services based on performance, cost, scalability, and reliability.
  • Implement monitoring and evaluation frameworks to assess AI effectiveness in production.

Engineering Excellence & Operations

  • Implement automated testing, CI/CD processes, monitoring, and observability across applications and AI systems.
  • Build reliable deployment patterns and operational frameworks for production environments.
  • Establish best practices around software quality, security, documentation, code review, and testing.
  • Continuously monitor application and agent performance to identify improvements and mitigate risks.

Required Qualifications

  • Bachelor's degree in Computer Science, Software Engineering, Information Systems, or a related technical discipline.
  • 8+ years of experience developing and deploying production-grade software applications.
  • Strong full-stack engineering experience across frontend and backend technologies.
  • Proven experience designing and building RESTful APIs and backend services.
  • Experience developing data-intensive applications or integrating with data platforms.
  • Hands-on experience building AI agents, agentic workflows, or LLM-powered applications.
  • Experience with retrieval-augmented generation (RAG), tool integrations, agent orchestration, and AI application frameworks.
  • Experience integrating AI systems with APIs, databases, enterprise platforms, and external services.
  • Frontend development experience with modern JavaScript frameworks.
  • Experience using AI-assisted development tools as part of the engineering workflow.
  • Experience implementing agent memory, context management, retrieval, and evaluation systems.
  • Experience with cloud-native software development and deployment.

Preferred Qualifications

  • Experience working with modern data lake, lakehouse, or analytics platform architectures.
  • Experience with infrastructure-as-code, CI/CD automation, and cloud-native deployment strategies.
  • Experience working within Agile or Scrum software delivery environments.
  • Experience deploying AI applications on public cloud platforms.

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