Director of Engineering - AI
Remote · USJob$200–239K/yrPosted 3 days agoStill listed 2 days ago
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Job overview
The Director of Engineering – AI will collaborate with management, customers, and internal teams to create and implement the AI strategy, drive design and development of AI systems, ensure security and privacy compliance, manage AI projects, improve customer satisfaction, and expand AI product features and automation.
Skills & qualifications
Skills
Qualifications
Full job description
Job Details: Job Location: California - Mountain View, CA, Salary Range: $200000.00 - $239200.00Salary/year, Your responsibilities will include:
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Collaborate with Management, Customers and Internal teams for the creation and implementation of the AI strategy
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Drive the design and development of AI systems, products, and solutions aligned with the AI strategy
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Ensure compliance with security and privacy standards, regulations and guidelines related to PII and PHI data in the usage of AI and machine learning tools and services, so that Company and Customer data are protected
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Day to day management of AI related projects and products
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Drive high customer satisfaction through continuous improvement of the AI products and solutions based on evaluation and feedback
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Enhance and expand the scope of AI products and solutions by adding features, functionality and automation
- Employee will be eligible to telecommute. Qualifications: Requires Bachelor’s degree computer science or related field and 6+ years of experience in I.T. Management, software development or related occupations
Requires proficient knowledge of:
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Design and delivery of enterprise systems using Cloud & Container Platforms like Microsoft Azure Cloud, AWS Cloud, Kubernetes, and Docker
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Development efforts for microservices-based applications
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Programming languages like Java and Python
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Proficiency knowledge of frameworks like Node.js, Spring Boot, Flask, and FastAPI and databases like PostgreSQL, Oracle, DB2, and Neo4j
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Implementing Artificial Intelligence / Machine Learning (AI/ML) and Large Language Model-based capabilities
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Using Azure OpenAI, LangChain, and multi-agent orchestration frameworks
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Development of healthcare interoperability features
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Building API-driven and event-driven application components
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Organizational security and compliance practices
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Secure coding principles, architecture guidelines, and DevSecOps processes
- Proficiency can be gained through education or experience.
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