What are the responsibilities and job description for the AI Engineer position at Jobs via Dice?
Dice is the leading career destination for tech experts at every stage of their careers. Our client, Sincera Technologies, Inc., is seeking the following. Apply via Dice today!
Job Title: Senior AI Engineer Google AI & Generative Intelligence
Location: [Paramus, NJ / Hybrid]
Role: Full-time
Experience Required: 10 15 Years in Software Engineering | 5 Years in Artificial Generative Intelligence
Job Description:
We are seeking a highly experienced Senior AI Engineer 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 Engineer, 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 junior engineers or interns in AI/ML domains.
Job Title: Senior AI Engineer Google AI & Generative Intelligence
Location: [Paramus, NJ / Hybrid]
Role: Full-time
Experience Required: 10 15 Years in Software Engineering | 5 Years in Artificial Generative Intelligence
Job Description:
We are seeking a highly experienced Senior AI Engineer 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 Engineer, 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 junior engineers or interns in AI/ML domains.