Senior Generative AI Architect

Coforge; Princeton (NJ); On-site; USD 160,000 - 230,000; Full time

Job summary

Coforge in Princeton, NJ is seeking a Senior Generative AI Architect to design and scale enterprise AI solutions. You will lead architecture, model development, and integration with existing systems.

The ideal candidate has 7+ years in AI/ML architecture, hands-on experience with TensorFlow, PyTorch and Hugging Face, and cloud deployment on AWS/Azure/GC.

This role emphasizes ethical AI practices, collaboration with data scientists and product teams, and documentation of standards.

Qualifications

• 7+ years in AI/ML architecture or related role.
• Proven design and deployment of generative AI models and solutions.
• Hands-on with TensorFlow, PyTorch, Hugging Face.
• Experience deploying AI on cloud platforms (AWS, Azure, GCP).
• Proficiency in Python, Java, or C++.
• Strong knowledge of machine learning and deep learning.

Responsibilities

• Design and maintain the architectural framework for generative AI solutions.
• Lead design, training, and deployment of generative AI models tailored to applications.
• Collaborate with software teams to integrate AI capabilities into existing systems.
• Ensure AI solutions are scalable, efficient, and optimized for performance.
• Implement and enforce ethical guidelines for AI development and deployment.
• Stay abreast of latest advancements in generative AI and related fields.
• Collaborate with data scientists, engineers, product managers and stakeholders.
• Create documentation for AI architectures, processes and best practices.
• Establish and maintain coding and architectural standards.

Skills

AI/ML architecture

Generative AI expertise

Cloud deployment experience

Programming: Python/Java/C++

ML & deep learning knowledge

Tools

TensorFlow

PyTorch

Hugging Face

AWS

Azure

Google Cloud

Job description

Job Title/Role: Senior Generative AI Architect

Location: Princeton, NJ

We at Coforge are hiring an experienced Senior Generative AI Architect with strong expertise in Generative AI, cloud-native architecture. The ideal candidate will have a hands-on background in Generative AI solutions, system design, and AI-driven customer experience solutions, with the ability to design, build, and scale intelligent solutions for enterprise clients.

Key Responsibilities:

• Architecture Design: Develop and maintain the architectural framework for generative AI solutions, ensuring alignment with business goals and technical standards.
• Model Development: Lead the design, training, and deployment of generative AI models (e.g., GPT, DALL-E, Stable Diffusion) tailored to various applications such as content generation, data synthesis, and automation.
• Integration: Collaborate with software engineering teams to integrate generative AI capabilities into existing systems and workflows.
• Scalability & Performance: Ensure AI solutions are scalable, efficient, and optimized for performance across different platforms and environments.
• Ethical AI Practices: Implement and enforce ethical guidelines for AI development and deployment, addressing issues such as bias, fairness, and transparency.
• Research & Innovation: Stay abreast of the latest advancements in generative AI and related fields, incorporating new techniques and tools into the company's AI strategy.
• Collaboration: Work closely with data scientists, engineers, product managers, and other stakeholders to identify opportunities for AI-driven solutions and ensure successful project delivery.
• Documentation & Standards: Create comprehensive documentation for AI architectures, processes, and best practices.
• Establish and maintain coding and architectural standards.

Required Skills & Experience:

• Minimum of 7 years of experience in AI/ML architecture or a related role.
• Proven experience in designing and deploying generative AI models and solutions.
• Hands-on experience with AI frameworks and tools such as TensorFlow, PyTorch, Hugging Face, etc.
• Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and deploying AI solutions in cloud environments.
• Technical Skills: Proficiency in programming languages such as Python, Java, or C++.
• Strong understanding of machine learning algorithms, deep learning

Good to Have:

• Designing test strategies for deterministic and non-deterministic (AI) systems
• Establishing measurable benchmarks for LLM performance and system reliability