Lead AI Engineer, Business Operations

Jobtailor; Dallas (TX); On-site; USD 140,000 - 200,000; Full time

Job summary

Jobtailor is seeking an experienced AI Architect to lead end-to-end architectural efforts for AI/LLM-backed systems in production. You will own planning, design, build, deployment, and continuous improvement while ensuring governance and reliability in a Dallas-based environment.

The role requires strong leadership, hands-on Python and cloud experience, and the ability to mentor engineers across multiple initiatives. Join a team shaping AI-enabled products at Jobtailor.

Qualifications

• 5+ years of software engineering and architecture experience with full-stack focus.
• Hands-on AI/LLM-backed systems in production.
• Experience architecting solutions from scratch to deployment and observability.
• Experience with AI development practices: model selection, fine-tuning, prompt engineering.
• Proficiency in Python and cloud platforms.
• Mentoring engineers and setting technical direction.
• Strong communication with technical and non-technical stakeholders.

Responsibilities

• Establish architectural patterns, evaluation practices, and deployment standards for the team.
• Recommend framework and model choices to set the team’s foundation.
• Collaborate with AI Enablement Manager to translate strategy into technical plans, backlogs, and buildable work.
• Own end-to-end solutions: planning, architecture, build, deployment, and production monitoring.
• Partner with data governance to ensure compliance, data quality, and standards.
• Build and maintain monitoring, evaluation, and regression systems for reliability.
• Lead and grow the team, onboarding AI Product Manager and AI Operations Specialists.

Skills

Software engineering

AI development practices

Python proficiency

Full-stack architecture

Team leadership

Strong communication

Mentoring engineers

Education

Bachelor's Degree in Computer Science

Tools

Cloud platforms

API design

Data infrastructure

Job description

• Establishes the architectural patterns, evaluation practices, and deployment standards for the team
• Makes framework and model recommendations that set the foundation for the team
• Collaborates with the AI Enablement Manager and business unit to optimize operational processes, owning the infrastructure architecture and translating strategic direction into technical plans, product life cycles, a prioritized backlog, and buildable work
• Owns solutions end-to-end: technically planning, architecture, build, and deployment, then continuously monitors, iterates, and improves them to keep them reliable in production
• Partners with data governance to ensure solutions meet compliance, data quality, and operational standards
• Builds and continuously maintains the monitoring, evaluation, and regression detection systems that keep production agents reliable over time, including logging, performance benchmarking, and feedback loops that surface drift early.
• Leads the team as it grows, onboarding new team members like AI Product Manager and AI Operations Specialists for intake, sequencing, stakeholder coordination, and product ownership of deployed solutions.

Requirements

• Bachelor's degree in Computer Science or related field, or equivalent experience
• 5+ years of software engineering and architecture experience with a strong full-stack foundation — backend services, API design, system integration, and data infrastructure
• Recent hands‑on experience architecting and delivering AI or LLM‑backed systems in production
• Experience architecting solutions from scratch and owning them through deployment, observability, testing, and ongoing reliability
• Experience with AI development practices — model selection, fine‑tuning, prompt engineering, evaluation frameworks, and understanding when each approach is the right fit
• Proficiency in Python; experience with cloud platforms
• Experience mentoring engineers and setting technical direction across multiple initiatives
• Strong communication skills with both technical and non‑technical stakeholders.

Core Competencies

Demonstrates expertise in software engineering and architecture, with a strong focus on AI and LLM‑backed systems. Capable of leading teams, optimizing operational processes, and ensuring compliance and reliability in production environments.

Highest-signal resume keywords

• Software Engineering Experience
• AI Development Practices
• Python Proficiency
• Full‑Stack Architecture
• Team Leadership

ATS Optimization Keywords

Hard Skills

• Software Engineering
• Architecture
• API Design
• System Integration
• Data Infrastructure
• AI Systems Architecture
• Model Selection
• Fine‑Tuning
• Prompt Engineering
• Testing

Soft Skills

• Strong Communication Skills
• Mentoring

Certifications & Qualifications

• Bachelor's Degree in Computer Science

Industry Keywords

• AI Enablement
• Data Governance
• Operational Standards
• Monitoring Systems
• Production Reliability

Tools & Technologies

• Cloud Platforms