Overview
We're seeking an experienced Solutions Architect to join our AI Automation team, focusing on
designing and implementing AI/ML/GenAI solutions. This role combines technical leadership
with hands-on development, requiring expertise in cloud platforms and artificial intelligence
technologies.

Key Responsibilities
- Design and architect end-to-end AI/ML solutions using GCP/Azure cloud platforms
- Lead technical teams in implementing AI/ GenAI automation solutions
- Accountable for removing roadblocks to delivery
- Collaborate with stakeholders to understand business requirements and translate them into
technical solutions
- Provide technical guidance to refine business requirements by deeply understanding customer
needs and proposing impactful solutions.
- Provide technical guidance and mentorship to development teams
- Develop proof-of-concepts and prototype solutions
- Create and maintain technical documentation and solution architectures
- Evaluate new AI/ML technologies and recommend adoption strategies

Required Qualifications
- 7+ years of experience in software architecture and development
- Proven experience with GCP and/or Azure cloud platforms
- Strong background in AI/ML solution development and implementation
- Strong experience in evaluating and utilizing LLMs and up to date with the latest evolutions in
the GenAI space
- Experience leading technical teams and managing complex projects
- Expertise in modern software development practices and methodologies
- Strong problem-solving and analytical skills
- Excellent communication skills with ability to explain complex technical concepts
- Managerial experience a plus

Technical Skills
- Cloud Platforms: GCP, Azure
- AI/ML Technologies: Machine Learning frameworks, GenAI platforms
- Software Architecture: Microservices, API design, distributed systems
- Development: Hands-on coding experience in relevant programming languages
- DevOps: CI/CD, Infrastructure as Code

Preferred Qualifications
- Cloud certifications (GCP Professional or Azure Solutions Architect)
- Experience with large-scale AI/ML deployments
- Background in data engineering and analytics
- Agile methodology experience
- Open-source contributions