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Generative Ai Jobs in Connecticut (NOW HIRING)

Staffingine LLC

Generative AI Architect

Orange, CT · On-site

Generative AI Architect Job Location: Orange, Connecticut Job Type: Contract * ideate/originate AI Use Cases within the organization. * Act as a strategic consultant to business leaders, facilitating ...

Iberdrola

Lead Engineer - Cloud & Gen AI

Orange, CT · On-site

$59.75 - $79.75/hr

Benefits - Avangrid Job Summary The Lead Engineer, Cloud and Generative AI (Artificial Intelligence) is the Subject Matter Expert (SME) with designing, implementing, and managing scalable cloud ...

Iberdrola

Lead Engineer - Cloud & Gen AI

Orange, CT · On-site

$59.75 - $79.75/hr

Benefits - Avangrid Job Summary The Lead Engineer, Cloud and Generative AI (Artificial Intelligence) is the Subject Matter Expert (SME) with designing, implementing, and managing scalable cloud ...

Iberdrola

Lead Engineer - Cloud & Gen AI

Orange, CT · On-site

$59.75 - $79.75/hr

Benefits - Avangrid Job Summary The Lead Engineer, Cloud and Generative AI (Artificial Intelligence) is the Subject Matter Expert (SME) with designing, implementing, and managing scalable cloud ...

Info Way Solutions

Gen AI Engineer

Hartford, CT · On-site

The role involves developing generative AI solutions and collaborating with teams to integrate these technologies into various applications. Responsibilities : • Design, develop, and deploy AI/ML ...

Deloitte

Oracle Gen AI Manager

Hartford, CT · On-site

Deloitte Oracle Generative AI Architect Managers help clients delineate strategy and vision, design and implement process and systems which align with business objectives and have a measurable impact ...

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Generative Ai information

What is a generative AI?

A Generative AI job involves developing, fine-tuning, or deploying AI models that can create content such as text, images, music, or code. Professionals in this field work with machine learning frameworks, large language models, and neural networks to improve AI-generated outputs. Roles may include AI researchers, machine learning engineers, prompt engineers, or data scientists specializing in generative models. These jobs require expertise in programming (Python, TensorFlow, PyTorch), data processing, and AI ethics.

What does a generative AI specialist do?

A Generative AI Specialist typically focuses on designing, training, and fine-tuning generative models, such as those used for text, image, or audio generation. You may be responsible for researching the latest advancements, preparing datasets, evaluating model performance, and collaborating closely with data engineers, product managers, and software developers to integrate solutions into products. In many organizations, you’ll also participate in brainstorming sessions to explore new applications of generative AI, contribute to technical documentation, and support model monitoring or improvement post-deployment. This role requires a blend of technical expertise and teamwork, offering a dynamic environment where you can have a direct impact on cutting-edge innovation.

What are the key skills and qualifications needed to thrive in the generative AI position?

To thrive as a Generative AI Specialist, you need a strong background in machine learning, deep learning, and natural language processing, often supported by a relevant degree such as computer science or data science. Expertise with frameworks like TensorFlow or PyTorch, proficiency in Python, and knowledge of cloud platforms are commonly expected, with additional certifications in AI or related fields seen as valuable assets. Strong problem-solving abilities, creativity, and effective communication skills set top candidates apart. These skills are crucial for designing, developing, and deploying advanced generative models that address real-world business needs.

Is generative AI a career?

Generative AI is a growing field with roles such as AI engineer, research scientist, and data scientist focused on developing and improving AI models. Careers in this area typically require skills in machine learning, programming, and data analysis, and often involve working with tools like neural networks and deep learning frameworks.

What are the most commonly searched types of Generative Ai jobs in Connecticut?

The most popular types of Generative Ai jobs in Connecticut are:

What are popular job titles related to Generative Ai jobs in Connecticut?

For Generative Ai jobs in Connecticut, the most frequently searched job titles are:

What job categories do people searching Generative Ai jobs in Connecticut look for?

The top searched job categories for Generative Ai jobs in Connecticut are:

What cities in Connecticut are hiring for Generative Ai jobs?

Cities in Connecticut with the most Generative Ai job openings:

Generative Ai jobs near you
Infographic showing various Generative Ai job openings in Connecticut as of August 2026, with employment types broken down into 74% Full Time, 19% Part Time, 2% Temporary, and 5% Contract. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution.

Generative AI Architect

Staffingine LLC

Orange, CT • On-site

Contractor

Re-posted 10 days ago

Job description

Job Title: Generative AI Architect
Job Location: Orange, Connecticut
Job Type: Contract

Job Description:

  • ideate/originate AI Use Cases within the organization.
  • Act as a strategic consultant to business leaders, facilitating AI ideation workshops to identify innovative, high-impact AI use cases. 
  • Analyze industry trends, emerging AI technologies, and competitive landscapes to drive disruptive AI innovation within the organization. 
  • Provide expert guidance on how AI can enhance business models, optimize operations, and create new revenue streams.            
  •  conduct AI use case feasibility assessment and develop AI solution architecture and implementation plan.
  • Conduct in-depth feasibility assessments of AI use cases, evaluating technical viability, data availability, and risks. Develop comprehensive technical documentation, including architecture diagrams, system specifications, and design decisions. Present AI solutions to senior stakeholders.
  • Collaborate with business stakeholders to translate AI opportunities into well-defined business cases with clear value propositions. 
  • Define the technical architecture, infrastructure, and data requirements for AI initiatives. Develop high-level solution designs that outline AI models, ML pipelines, and system integrations. Provide input on technology selection, including AI frameworks, cloud platforms (Azure, AWS), and MLOps tools. Define resource and skillset requirements for AI build projects. Estimate project costs, infrastructure needs, and timelines, assisting in budget planning for AI initiatives. 
  • lead the implementation of AI use cases, managing team of AI Engineers, Data Scientists, ML Ops engineers and others.
  • Ensure quality and schedule of AI use case delivery. Regularly communicate development progress with key stakeholders and receive feedback from them.
  • Make sure best coding practices/standards are being followed by the team, code reviews, technical troubleshooting, drive day to day development task prioritization, allocation & coordination for offshore team members via Jira based scrum process, lead technical coordination with onsite team.
  • Continuously optimize and tune generative models, retrieval algorithms, and pipelines to enhance performance and accuracy. Ensure AI solutions adhere to security, compliance, and privacy standards, particularly for data-sensitive applications. Drive organizational AI maturity by defining standards for model monitoring, performance evaluation, and continuous improvement.
  • Provide leadership in cloud architecture design, deployment, and scaling strategies, ensuring that AI systems are efficient, secure, and maintainable within the Azure/AWS ecosystem.
  • Governance & Risk Management – evaluate risks of AI use cases and suggest mitigations strategies.
  • Establish AI governance frameworks, ensuring adherence to best practices in AI ethics, model transparency, data privacy, etc.

Experience

  • 8-10 years of experience in the ideation, design and end-to-end implementation of AI solutions.
  • Proven track record of leading teams of AI engineers and reporting to senior leadership.
  • At least 5 years of hands-on experience working with Azure AI, Azure OpenAI, Azure Cognitive Services, and Azure Machine Learning. Experience with AWS is a plus.
  • Proven expertise in deploying machine learning models and AI applications in a cloud environment (Azure preferred, AWS experience is a plus).

Technical Skills:

  • Strong proficiency in Natural Language Processing (NLP) and deep learning techniques for building AI models.
  • Experience with large language models (LLMs) such as GPT, BERT, and OpenAI's fine-tuned models.
  • Knowledge of retrieval-based techniques, including semantic search, vector databases, and information retrieval systems.
  • Familiarity with APIs and cloud-based data storage solutions (e.g., Azure Blob Storage, Cosmos DB, etc.).
  • Experience with DevOps practices for machine learning, including CI/CD for AI systems, containerization (Docker), and orchestration (Kubernetes).

Additional Skills:

  • Solid understanding of cloud architecture, scalability, and security best practices in cloud computing.
  • Experience in AWS cloud services is a strong advantage (e.g., AWS Lambda, S3, SageMaker).
  • Familiarity with data pipeline technologies and distributed data processing frameworks (e.g., Spark, Hadoop) is a plus.
  • Excellent problem-solving skills and the ability to work in fast-paced environments.

Soft Skills:

  • Strong communication and collaboration skills, with the ability to explain complex AI concepts to non-technical stakeholders.
  • Leadership abilities to mentor teams and drive AI strategy in alignment with business goals.
  • Ability to work independently and in team settings, balancing multiple priorities.