Director of AI Automation
Confidential · United States
- Hybrid
- Full-time
- $375,000 / year
- United States
Tailored resume — keyword-matched to this role.
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Job highlights
- Lead AI/ML development lifecycle.
- Build and deploy scalable AI/ML models.
- Own AI product roadmap and strategy.
- Mentor and grow a high-performing AI team.
- Ensure responsible AI practices and compliance.
About the role
About Us
We are a staffing services technology company that helps organizations design, build, and scale digital products and engineering capabilities. Our teams deliver end-to-end software development, engineering, and design services, and we provide flexible staffing solutions to augment internal teams with specialized talent—quickly and reliably.
The Role
We are seeking an innovative and resilient Director of AI Development to lead our distributed engineering team. Whether you’re a seasoned Machine Learning Architect ready to design complex neural networks or an NLP specialist optimizing large language models, you’ll have a pivotal role on our technology ladder. You will lead the full AI/ML development lifecycle, bridging data science, backend engineering, and product needs to build intelligent systems that solve real-world problems. You will set strategy, define roadmaps, mentor engineers, and drive high-impact AI initiatives across multiple client engagements and internal platforms.
What You’ll Do
- Build & Solve: Design, develop, and deploy scalable AI/ML models and systems. Diagnose model performance issues, optimize inference times, and guide integration of AI features into core products with clear, measurable outcomes.
- Leadership & Collaboration: Own the AI product roadmap in collaboration with Product Managers, Data Scientists, and Backend Engineers. Lead cross-functional squads in an Agile environment to operationalize prototypes, share technical insights, and refine API documentation.
- Quality, Speed & Excellence: Ensure high model accuracy, low latency, and robust operationalization. Manage multiple workstreams with a disciplined backlog, rigorous code quality standards, and reproducible experiments. Establish and promote engineering best practices (CI/CD, testing, instrumentation, observability) across AI initiatives.
- People & Mentorship: Build, coach, and grow a high-performing AI/ML engineering team; foster a culture of learning, experimentation, and psychological safety. Promote best practices for remote collaboration, knowledge sharing, and career development.
- Governance & Risk: Ensure compliance with data handling, privacy, and security requirements; address regulatory considerations relevant to client industries. Drive responsible AI practices, including bias monitoring, interpretability, and auditability.
What We’re Looking For
Experience
- 10+ years of professional experience in Software Engineering, Data Science, or Machine Learning in production environments.
- Prior leadership or management experience overseeing AI/ML programs or teams.
Education
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Mathematics, or a related field (or equivalent practical experience).
Technical Aptitude
- Proficiency with Python and modern ML frameworks (PyTorch, TensorFlow, Keras, scikit-learn).
- Familiarity with MLOps tools (MLflow, Kubeflow, Weights & Biases) and cloud ML services.
- Experience with deployment and monitoring of AI systems in production.
- Excellent written and verbal communication; ability to translate complex mathematical concepts into actionable business insights for non-technical stakeholders.
Problem Solving
- Strong analytical mindset; ability to diagnose root causes of model failures and to drive lasting improvements.
Engineering & Organizational Practices
- Solid grounding in software engineering principles (CI/CD, Git, Docker, unit/integration testing); ability to deliver clean, maintainable, scalable code and systems.
Remote Readiness
- Proven capability to work effectively in a distributed, asynchronous environment; self-motivated, disciplined, and communicative.
Adaptability
- Calm under pressure when experiments fail; pivot strategies quickly and convert setbacks into learning opportunities.
Bonus Points
- Certifications: AWS Certified Machine Learning – Specialty, Google Professional Machine Learning Engineer, or DeepLearning.AI specializations.
- Specialized Skills: Experience with LLMs, Retrieval-Augmented Generation (RAG), vector databases (e.g., Pinecone, Milvus), or reinforcement learning.
- Industry Knowledge: Prior AI applications in FinTech, Healthcare, E-commerce, SaaS, or other relevant sectors.
- Thought Leadership: Technical blog writing, open-source contributions, conference presentations (e.g., NeurIPS, ICML, CVPR).
- Cloud & Infrastructure: Experience managing GPU clusters, serverless inference, and multi-cloud deployments (AWS, Azure, GCP).
- Compliance & Privacy: Familiarity with regulated environments (HIPAA, SOC 2), and applying differential privacy or federated learning techniques.
Compensation & Benefits
We believe in paying top-of-market rates for top-tier talent. The base salary range for this role is $300,000 to $375,000, with exact placement determined by your skills, years of experience, and interview performance. We also offer a comprehensive benefits package, performance incentives, and professional development opportunities.
- Additional Benefits:
- Equity: Competitive stock option package.
- Remote Setup: Home office stipend to get your workspace set up perfectly.
- Health: Comprehensive medical, dental, and vision insurance.
- Time Off: Flexible PTO policy + Company Holidays.
- Growth: Annual learning and development budget.
- Retirement: 401(k) matching plan.
Key skills/competency
- AI Development
- Machine Learning
- Python
- MLOps
- Cloud ML Services
- Large Language Models
- Data Science
- Software Engineering
- Team Leadership
- Agile Methodologies
Skills & topics
- Director of AI
- AI Automation
- Machine Learning
- Python
- PyTorch
- TensorFlow
- MLOps
- Data Science
- Software Engineering
- Team Leadership
- Agile
- Remote
How to get hired
- Tailor your resume: Highlight 10+ years of AI/ML experience, leadership, and specific technical skills like Python, PyTorch, and MLOps tools.
- Showcase leadership: Emphasize experience managing AI/ML programs and teams, and your ability to mentor and grow talent.
- Demonstrate technical depth: Provide examples of designing, developing, and deploying scalable AI/ML models in production, including performance optimization.
- Highlight remote work skills: Stress your self-motivation, discipline, and strong communication in distributed environments.
- Prepare for technical and behavioral questions: Be ready to discuss AI strategy, problem-solving approaches, and collaboration in an Agile setting.
Technical preparation
Master Python and ML frameworks.,Practice with MLOps and cloud ML services.,Build and deploy production AI systems.,Understand CI/CD, testing, and observability.
Behavioral questions
Discuss leading distributed AI teams.,Explain how you set AI strategy.,Describe a complex AI problem solved.,How do you foster team learning?
Frequently asked questions
- What is the salary range for the Director of AI Automation role at this company?
- The base salary range for the Director of AI Automation role is $300,000 to $375,000 annually. The exact placement within this range will depend on your skills, years of experience, and interview performance. This range reflects our commitment to paying top-of-market rates for exceptional talent.
- What are the key technical skills required for the Director of AI Automation position?
- The Director of AI Automation role requires proficiency in Python and modern ML frameworks such as PyTorch, TensorFlow, Keras, and scikit-learn. Familiarity with MLOps tools like MLflow, Kubeflow, and Weights & Biases, as well as cloud ML services and production deployment/monitoring of AI systems, is also essential.
- Does this Director of AI Automation role offer remote work options?
- Yes, this role is designed for effective work in a distributed, asynchronous environment. The company emphasizes remote collaboration and provides a home office stipend to ensure you have a well-equipped workspace. Successful candidates must be self-motivated, disciplined, and communicative.
- What kind of leadership experience is expected for the Director of AI Automation role?
- We are looking for candidates with prior leadership or management experience specifically overseeing AI/ML programs or teams. This includes experience in setting strategy, defining roadmaps, mentoring engineers, and driving high-impact AI initiatives, as well as building, coaching, and growing a high-performing AI/ML engineering team.
- What are the 'Bonus Points' for the Director of AI Automation application?
- Bonus points for the Director of AI Automation role include relevant certifications (AWS, Google ML, DeepLearning.AI), specialized skills in LLMs, RAG, vector databases, or reinforcement learning, industry-specific AI application experience (FinTech, Healthcare, etc.), thought leadership (blogs, open-source, presentations), cloud/infrastructure management (GPUs, multi-cloud), and familiarity with regulated environments (HIPAA, SOC 2).
- What benefits are offered to the Director of AI Automation at this company?
- In addition to competitive salary and potential equity, benefits include a comprehensive health package (medical, dental, vision), a flexible PTO policy, a home office stipend, an annual learning and development budget, and a 401(k) matching plan. This reflects our commitment to supporting our employees' well-being and growth.