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AI​/ML Engineer

Job in Santa Clara, Santa Clara County, California, 95053, USA
Listing for: Siri InfoSolutions Inc
Full Time position
Listed on 2026-09-11
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Backend Developer, Cloud Engineer - Software
Salary/Wage Range or Industry Benchmark: 120000 - 180000 USD Yearly USD 120000.00 180000.00 YEAR
Job Description & How to Apply Below

Must Have Technical/Functional

Skills:

  • Must have strong hands-on experience in Python programming, API development, and cloud-native application development (4 Years Minimum).
  • Must have experience building prototypes, solution accelerators, and enterprise integrations using cloud technologies.
  • Must have two years' experience with Google Cloud Platform (GCP), Vertex AI, Gemini APIs, or similar AI platforms.
  • Must have experience in Prompt Engineering, LLM application development, and AI solution implementation.
  • Must have experience developing Agentic AI workflows, AI agents, and orchestration frameworks.
  • Must have experience with REST APIs, microservices, and third-party system integrations.
  • Must have experience working with containerization, CI/CD, and production deployment practices.
  • Must possess strong stakeholder communication and customer-facing solutioning skills
Roles & Responsibilities:
  • Design and develop AI-powered prototypes, accelerators, and customer-facing solutions.
  • Build and integrate applications using Gemini APIs, Vertex AI, and Google Cloud services.
  • Develop agentic workflows, AI assistants, and multimodal solution demonstrations.
  • Collaborate with customers, partners, and cross-functional teams to validate business use cases.
  • Translate business requirements into scalable technical architectures and solutions.
  • Build Proof of Concepts (PoCs) and demonstrate business value through rapid prototyping.
  • Support deployment, optimization, and troubleshooting of AI solutions in cloud environments.
  • Stay current with emerging AI technologies and apply them to customer scenarios
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