Senior Engineer Artificial Intelligence

About the Role

This position focuses on building prototypes, integrations, and solution accelerators using cloud and API-based technologies, particularly within AI application environments like Gemini APIs and Vertex AI. The role involves developing agentic workflows, lightweight integrations, and multi-modal demonstrations to validate technical feasibility and drive business value.

Responsibilities

• Build working prototypes, proof points, and multi-modal demonstrations using Gemini APIs, Vertex AI, and Google Cloud.
• Develop agentic workflows and lightweight integrations to validate technical feasibility for customer-specific scenarios.
• Own technical validation across deal cycles by rapidly translating Gemini Enterprise capabilities into deployable prototype outcomes.
• Apply prompt engineering and Google Gemini ADK to improve prototype quality, usability, and business relevance.
• Translate prototype outcomes into value narratives that support decision-making and accelerate customer progression.
• Collaborate cross-functionally to connect technical validation to business value.
• Manage stakeholder expectations and translate customer requirements into actionable technical outcomes.
• Communicate technical concepts clearly to business and non-technical stakeholders.
• Maintain ownership of delivery, timelines, and quality in ambiguous or fast-moving environments.
• Prioritize multiple prototypes, demos, or validation requests effectively.
• Document and report progress with discipline, ensuring customer-centric outcomes.

Requirements

• 5 to 7 years of total experience, including 3 to 5 years of AI experience.
• Strong hands-on engineering skills with experience building prototypes, integrations, or solution accelerators using cloud and API-based technologies.
• Experience with Gemini APIs, Vertex AI, Google Cloud, prompt engineering, or similar AI application environments.
• Ability to develop agentic workflows, lightweight integrations, and multi-modal demonstrations for customer or partner scenarios.
• Strong communication and cross-functional collaboration skills.
• Bachelor’s degree in Engineering or Computer Science.
• Strong written and spoken English.

Preferred Qualifications

• Google Professional ML Engineer certification.
• Gemini Enterprise Partner Certification.
• Google Associate Cloud Engineer certification.
• Applied analytics experience and the ability to convert prototype outcomes into clear value narratives.

Benefits

• Discretionary Annual Incentive.
• Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans.
• Family Support: Maternal & Parental Leaves.
• Insurance Options: Auto & Home Insurance, Identity Theft Protection.
• Commuter Benefits & Certification & Training Reimbursement.
• Time Off: Vacation, Time Off, Sick Leave & Holidays.
• Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.

Pay

$120,000-$145,000 a year