Lead AI Solutions Engineer
Overview
We are seeking a highly skilled Lead AI Solutions Engineer to design, develop, and deploy advanced AI-driven solutions that solve complex business challenges. This role combines deep technical expertise with leadership and stakeholder engagement to deliver scalable, production-ready systems.
The ideal candidate will bridge the gap between cutting-edge machine learning and real-world applications, working closely with cross-functional teams to translate requirements into impactful AI solutions.
Key Responsibilities
- Lead the design, development, and deployment of AI/ML solutions from concept to production
- Architect scalable systems and ensure reliability, performance, and maintainability
- Collaborate with data scientists, engineers, and business stakeholders to identify and prioritize use cases
- Build and optimize machine learning models, including training, evaluation, and monitoring
- Develop proof-of-concept solutions and prototypes to demonstrate business value
- Define and implement best practices for AI development, MLOps, and deployment pipelines
- Translate complex technical concepts into clear business insights for non-technical audiences
- Mentor and guide junior engineers and contribute to team capability building
- Stay current with emerging AI technologies and incorporate relevant innovations into solutions
- Document architecture, workflows, and technical decisions
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field
- Strong experience in machine learning, deep learning, or applied AI
- Proficiency in programming languages such as Python or Java
- Hands-on experience with frameworks such as TensorFlow, PyTorch, or similar
- Experience designing and deploying production-grade AI systems
- Solid understanding of data engineering, APIs, and system integration
- Familiarity with cloud platforms and scalable infrastructure
Skills and Competencies
- Strong problem-solving and analytical thinking
- Excellent communication and stakeholder management skills
- Ability to balance technical depth with business impact
- Experience leading projects or mentoring team members
- Knowledge of MLOps, model lifecycle management, and deployment best practices
What Success Looks Like
- Delivery of high-impact AI solutions aligned with business objectives
- Scalable, reliable systems operating in production environments
- Effective collaboration across technical and non-technical teams
- Continuous improvement in model performance and system efficiency
Summary
This role is critical to delivering production-ready AI systems that create measurable value. It requires a blend of engineering excellence, strategic thinking, and leadership to ensure successful deployment and adoption of AI across the organization.