AI Collaborator, Inc. · 2 days ago
AI Collaborator Senior AI Solutions Architect – Consumer Electronics
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Artificial Intelligence (AI)Business Development
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Responsibilities
Collaborate closely with sales teams to assess client needs and create tailored technical solutions.
Develop and communicate solution architectures that align with client goals and existing infrastructure.
Engage with clients to deliver comprehensive AI deployment strategies and handle complex technical challenges.
Recommend new offerings and collaborate with the product team to enhance our portfolio.
Maintain a strong feedback loop with engineering to ensure technical soundness and scalability.
Conduct hands-on demos, create technical documentation, and deliver client-facing training sessions.
Evaluate emerging technologies for potential integration and recommend best practices.
Advocate for responsible AI innovation, ensuring solutions uphold AI Collaborator's core principles.
Qualification
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Required
Bachelor’s or Master’s degree in Computer Science, Engineering, or related fields.
7+ years of experience in AI/ML solutions, software engineering, or related fields.
Proven ability to articulate complex technical concepts in presales engagements.
Proficiency in deep learning frameworks (e.g., TensorFlow, PyTorch) and AI development.
Expertise in at least one modern programming language, such as Python, Go, C++, Bash, etc.
Extensive expertise in AWS, Azure, or GCP (preference for AWS).
Experience with DevOps frameworks such as Docker, Kubernetes, and CI/CD pipelines.
Working knowledge of Tableau for data visualization and Snowflake for data warehousing and analytics.
Strong communication skills, able to collaborate effectively with technical and non-technical stakeholders.
Knowledge of databases (SQL, NoSQL) and distributed system technologies (Kafka, Redis, Elastic Search, Airflow, etc).
Experience designing data architectures and integrating AI solutions at scale.
Working knowledge of vector databases and LLM customization.
Demonstrated experience in enterprise AI deployments, including DataOps and MLOps.