AI/ML Engineer

Siri InfoSolutions Inc; Santa Clara (CA); On-site; USD 120,000 - 180,000; Full time

Job summary

Siri InfoSolutions Inc. is seeking an experienced AI/ML engineer to design and deliver AI-powered prototypes, accelerators, and customer-facing solutions.

You will build applications using Gemini APIs, Vertex AI, and Google Cloud services, and develop agentic workflows and multimodal demonstrations. Collaborating with customers and cross-functional teams, you will translate business needs into scalable architectures, create PoCs, and support deployment and optimization in cloud environments;

Qualifications

• 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.

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

Skills

Python programming

API development

Cloud-native development

GCP

Vertex AI

Gemini APIs

AI platforms

Prompt engineering

LLM app development

AI solution implementation

Agentic AI workflows

AI agents

Orchestration frameworks

REST APIs

Microservices

Third-party integrations

Containerization

CI/CD

Deployment practices

Stakeholder communication

Customer-facing solutioning

Tools

Vertex AI

Gemini APIs

Google Cloud Platform

Job description

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