What are the responsibilities and job description for the AI Architect position at Sincera Technologies, Inc.?
AI Architect Google AI & Generative Intelligence
Location: [Jersey City, NJ / Hybrid]
Experience Required: 10 15 Years in Software Engineering | 5 Years in Artificial Generative Intelligence
Job Description:
We are seeking a highly experienced AI Architect with deep expertise in Google AI technologies, Generative AI, and Large & Small Language Model (LLM/SLM) development. The ideal candidate brings 10 15 years of broad software engineering experience, with the last 5 years focused exclusively on Artificial Generative Intelligence, including designing, building, deploying, and monitoring production-grade AI systems. This role demands mastery of the Google ecosystem including Google Workspace, Google Agent Development Kit (ADK), and Vertex AI alongside a strong command of modern LLM/SLM frameworks, cloud-native infrastructure, and MLOps best practices.
Required Qualifications
10 15 years of overall software engineering experience.
5 years of hands-on experience in Artificial Generative Intelligence, including LLMs, SLMs, RAG, and multi-agent systems.
Deep expertise in Google AI ecosystem: Gemini, Vertex AI, Google ADK, Google AI Studio, and Google Workspace integrations.
Proficiency in Python (primary) and familiarity with Node.js.
Strong background in cloud-native development on Google Cloud Platform.
Demonstrated experience with model fine-tuning (LoRA, QLoRA, PEFT) and model evaluation frameworks.
Solid understanding of MLOps, CI/CD for AI systems, and production deployment best practices.
Experience with multi-agent AI architectures using Semantic Kernel, or LangGraph.
Preferred Qualifications
Google Cloud Professional certifications ( Professional ML Architect, Professional Cloud Architect).
Contributions to open-source AI/ML projects.
Experience with edge AI deployments and hybrid cloud-edge inference.
Familiarity with synthetic data generation pipelines.
Prior experience mentoring engineers or interns in AI/ML domains.
Required Qualifications
10 15 years of overall software engineering experience.
5 years of hands-on experience in Artificial Generative Intelligence, including LLMs, SLMs, RAG, and multi-agent systems.
Deep expertise in Google AI ecosystem: Gemini, Vertex AI, Google ADK, Google AI Studio, and Google Workspace integrations.
Proficiency in Python (primary) and familiarity with Node.js.
Strong background in cloud-native development on Google Cloud Platform.
Demonstrated experience with model fine-tuning (LoRA, QLoRA, PEFT) and model evaluation frameworks.
Solid understanding of MLOps, CI/CD for AI systems, and production deployment best practices.
Experience with multi-agent AI architectures using Semantic Kernel, or LangGraph.
Preferred Qualifications
Google Cloud Professional certifications ( Professional ML Architect, Professional Cloud Architect).
Contributions to open-source AI/ML projects.
Experience with edge AI deployments and hybrid cloud-edge inference.
Familiarity with synthetic data generation pipelines.
Prior experience mentoring engineers or interns in AI/ML domains.