AI & Data Platform Engineering Manager

Jobtailor; Colorado; Hybrid; USD 180,000 - 240,000; Full time

Job summary

Jobtailor is seeking an experienced AI/ML Platform Leader to direct the enterprise AI platform and MLOps teams. You will guide generative AI architectures, model routing, and workflow orchestration while aligning with business platforms and governance requirements.

You will mentor senior engineers, drive long-term technical roadmaps, and coordinate cross-functional efforts in a hybrid work setting. Travel up to 20% is required.

Qualifications

• Bachelor’s degree in computer science, mathematics, statistics, engineering, or related STEM field.
• 6-8+ years of experience in AI/ML or software engineering.
• 2+ years in a management role.
• Relevant experience can substitute for required educational qualifications; without a degree, minimum 13 years of related experience is required.
• Higher level relevant degree may substitute for experience.
• Demonstrated success leading engineering teams and delivering complex technical programs.
• Expertise in generative AI/LLM techniques.
• Familiarity with supervised and unsupervised ML for data platform use cases.

Responsibilities

• Lead the AI/LLM Platform and MLOps engineering team delivering the enterprise AI platform.
• Provide technical guidance on LLM and generative AI architectures, including the LLM gateway, model routing, and agent/workflow orchestration.
• Oversee integration of ML models and AI capabilities into enterprise systems and business platforms.
• Establish validation, verification, and compliance processes.
• Manage resourcing, budgeting, schedules, and risk mitigation.
• Mentor senior engineers and technical leads.
• Drive AI/LLM platform capability development and own the long-term technical roadmap.
• Lead multi-team engineering operations in a hybrid environment.
• Participate in integration events, customer reviews, and working groups.
• Travel up to 20% for program execution and external coordination.
• Provide technical escalation support for complex ML challenges.

Skills

AI/ML Leadership

Generative AI/LLM

ML Pipeline Architecture

Data Governance

Model Routing

Workflow Orchestration

Validation & Verification

Risk Mitigation

Technical Roadmap

Cross-Functional Execution

Education

Bachelor’s degree in CS/Math/Engineering

Tools

AWS

Google Cloud

Azure

MLOps Tools

Enterprise Systems

Job description

• Lead the AI/LLM Platform and MLOps engineering team delivering the enterprise AI platform
• Provide technical guidance on LLM and generative AI architectures, including the LLM gateway, model routing, and agent/workflow orchestration
• Oversee integration of ML models and AI capabilities into enterprise systems and business platforms
• Establish validation, verification, and compliance processes
• Manage resourcing, budgeting, schedules, and risk mitigation
• Mentor senior engineers and technical leads
• Drive AI/LLM platform capability development and own the long-term technical roadmap
• Lead multi-team engineering operations in a hybrid environment
• Participate in integration events, customer reviews, and working groups
• Travel up to 20% for program execution and external coordination
• Provide technical escalation support for complex ML challenges

Requirements

• Bachelor’s degree in computer science, mathematics, statistics, engineering, or related STEM field
• 6-8+ years of experience in AI/ML or software engineering
• 2+ years in a management role
• Relevant experience can substitute for required educational qualifications; without a degree, minimum 13 years of related experience is required
• Higher level relevant degree may substitute for experience
• Demonstrated success leading engineering teams and delivering complex technical programs
• Expertise in generative AI/LLM techniques
• Familiarity with supervised and unsupervised ML for data platform use cases
• Experience architecting and optimizing ML pipelines and high-performance systems
• Strong understanding of security, compliance, and data governance requirements, including CMMC and data classification
• Ability to drive cross-functional execution across software, data, and business platform teams
• AWS Machine Learning Specialty, Google Professional ML Engineer, Azure AI Engineer Associate, or equivalent hands-on experience with a major cloud AI/ML platform
• CMMC/NIST SP 800-171 awareness or equivalent compliance training
• U.S. citizenship, lawful permanent residence, protected individual status, or eligibility to obtain required U.S. government authorizations

Core Competencies

Demonstrates expertise in leading AI/LLM platform development and MLOps engineering, with a strong focus on generative AI architectures and compliance processes. Proven ability to manage engineering teams, drive cross-functional execution, and oversee complex technical programs.

Highest-signal resume keywords

• AI/ML Engineering Leadership
• Generative AI/LLM Expertise
• ML Pipeline Architecture
• AWS Machine Learning Specialty
• CMMC Compliance Awareness

Hard Skills

• AI/ML Engineering
• Generative AI Techniques
• ML Pipeline Optimization
• Data Governance
• Model Routing
• Workflow Orchestration
• Validation and Verification Processes
• Risk Mitigation
• Technical Roadmap Development
• Cross-Functional Execution

Soft Skills

• Mentoring
• Technical Guidance
• Collaboration
• Problem Solving
• Communication

Certifications & Qualifications

• AWS Machine Learning Specialty
• Google Professional ML Engineer
• Azure AI Engineer Associate
• CMMC/NIST SP 800-171 Compliance Training

Industry Keywords

• AI Platform
• LLM Gateway
• Hybrid Environment
• Data Classification
• Compliance Standards

Tools & Technologies

• AWS
• Google Cloud
• Azure
• MLOps Tools
• Enterprise Systems