Full Stack AI Engineer with Solution Architecture experience

Reveille Technologies,Inc

Houston (TX)

On-site

USD 120,000 - 160,000

Full time

21 hours ago
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Job summary

Reveille Technologies, Inc. in Houston, Texas is seeking a hands-on Senior Full Stack AI Engineer with Solution Architect experience to design and guide the build of scalable SaaS applications for complex, real-world industrial environments.

You will own the architecture of cloud-native, microservice-based platforms end-to-end — from data modeling and infrastructure through deployment — while guiding emerging AI technologies.

Qualifications

  • BS in Computer Science or related STEM field.
  • Experience with AI assistant tools like Claude Code and GitHub Copilot.
  • Experience with AI/ML frameworks (LangChain, AutoGen, CrewAI).
  • Experience with specification-driven development (SDD).
  • Proven track record in microservice architecture for scalable apps.
  • Cloud-native tech (Azure or AWS), Docker, Kubernetes, Terraform, Ansible.
  • SQL and NoSQL databases experience.
  • Fluency in Node.js, Python or React.
  • Advanced English communication skills.

Responsibilities

  • GenAI & Autonomous Agents development and deployment.
  • Build autonomous agents that plan tasks and execute tools.
  • Advanced RAG pipelines combining semantic search with knowledge traversal.
  • Integrate agents with engineering tools, simulators, databases, and knowledge sources.
  • Collaborate with domain experts to align agent behavior with requirements.
  • Implement safeguards for accuracy, traceability, and reliability of AI outputs.
  • Optimize prompting, agent orchestration, and performance.
  • Develop high-performance Python services (FastAPI) for live data.
  • Design and implement cloud-native SaaS architectures in production.
  • Architect cloud infra on Azure/AWS; use Docker, Kubernetes, Terraform, Ansible.
  • Create architecture diagrams and maintain documentation.
  • Guide data modeling across SQL/NoSQL databases.
  • Partner with product, sales, customer, and engineering teams.
  • Deliver fast without compromising code quality or API design.

Skills

Advanced English communication
Fluency in Node.js/Python/React
Specification-driven development (SDD)
Microservice architecture experience
Hands-on senior full stack AI engineer

Education

BS in Computer Science or related STEM field

Tools

Claude Code
GitHub Copilot
LangChain
AutoGen
CrewAI
Azure
AWS
Docker
Kubernetes
Terraform
Ansible
SQL
NoSQL
Node.js
Python
React

Job description

Title: Full Stack AI Engineer (with Solution Architecture experience)

Location: Houston TX

Duration: Long Term Contract

Required Skills & Qualifications
  • BS in Computer Science or a related STEM field.
  • Strong experience with AI assistant tools like Claude Code and GitHub Copilot, and using harness engineering principles.
  • Strong experience of AI/ML frameworks, such as LangChain, AutoGen, CrewAI and others.
  • Proven experience with specification-driven development (SDD) methodologies.
  • Proven track record designing and implementing performant, resilient, and scalable applications following microservice architecture in real-world scenarios.
  • Experience with cloud-native technologies (Azure and/or AWS, Docker, Kubernetes, Terraform, Ansible).
  • Experience with database technologies (SQL and NoSQL).
  • Fluency in one or more of: Node.js, Python, React
  • Advanced English communication skills.
Preferred Skills:
  • UI experience such as React.
  • Prior experience with software development in the Oil & Gas industry.
  • AI Technical trainings and Certifications such as: ClaudeCode Architect and others
Job Summary:

looking for a hands-on Senior Full stack AI engineer with Solution Architect experience to design and guide the build of performant, resilient, and scalable SaaS applications for complex, real-world industrial environments. You will own the architecture of cloud-native, microservice-based platforms end-to-end — from data modeling and infrastructure through deployment — while also shaping how emerging AI and agentic technologies are incorporated into our solutions. This is an individual-contributor role with significant technical influence: you will guide engineering teams on architectural decisions, collaborate across product, sales, and customer teams, and remain a hands-on contributor to development.

Key Responsibilities
  • GenAI & Autonomous Agents
  • Build Autonomous Agents: Deploy stateful agents (using LangGraph) that plan tasks, query Knowledge Graphs, and execute tools without hallucinating.
  • Advanced RAG: Build Graph-RAG pipelines that combine semantic search with structured knowledge traversal for grounded answers.
  • Build agents capable of integrating with engineering tools, simulators, databases, and knowledge sources.
  • Collaborate with domain experts to align agent behavior with technical expectations and constraints.
  • Implement safeguards to ensure accuracy, traceability, and reliability of AI-generated outputs.
  • Continuously optimize prompting, agent orchestration, and performance under real-world conditions.
  • High-Performance APIs: Build low-latency Python services (FastAPI) to serve live data to frontend and AI models.
  • Solution Architecture: Design and implement performant, resilient, and scalable SaaS applications following microservice architecture in production environments.
  • Cloud & Infrastructure: Architect cloud-native solutions on Azure and/or AWS using containers (Docker), orchestration (Kubernetes), and infrastructure-as-code (Terraform, Ansible).
  • Documentation: Produce detailed architecture diagrams and documentation that accurately capture the current state of applications and new feature implementations.
  • Data Architecture: Guide data modeling and database design decisions across relational and NoSQL systems (SQL Server, PostgreSQL, MongoDB).
  • Cross-Functional Influence: Partner with product management, sales, customer, and engineering teams to align technical solutions with business needs.
  • Rapid Delivery: Adopt a “deliver fast” mentality without compromising code quality, testing, or API design standards.
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