Job Title: AI/ML Architect
Work Location: Hartford CT
Duration: Longterm
Job Description
We are seeking a highly experienced Solution Architect to lead the design and implementation of patient solution systems within a pharmaceutical or life sciences environment. The ideal candidate will have a strong background in Salesforce Marketing TIBCO API integrations and Adobe Experience Manager (AEM).
Key Responsibilities:
We are seeking a Senior AI Architect to lead the design development and governance of cutting-edge AI solutions. This role requires both hands-on technical expertise and strategic leadership-driving innovation while ensuring compliance security and scalability across our AI ecosystem.
Key Responsibilities
- AI Leadership & Strategy:
- Lead our end-to-end AI development-balancing hands-on model design and implementation with guiding and mentoring the broader AI engineering and research teams.
- Architecture Design and Deployment:
- Design build and deploy production-grade machine learning models-including LLMs-on the Google Cloud Platform (Vertex AI) using Python and related frameworks.
- Collaboration & Ecosystem Management:
- Partner closely with internal AI teams Google and other technology vendors to sustain momentum drive innovation and align with evolving best practices.
- Governance Security and AIRB Compliance:
- Own and execute AI governance processes including AI Risk Board (AIRB) reviews data security compliance and ethical AI considerations across all AI initiatives.
- Model Development & Evaluation:
- Design and implement models for Conversational AI leveraging Google CCAI/CES components. Lead model evaluation using robust Eval frameworks and metrics to ensure reliability accuracy and fairness.
- Advanced Architectures:
- Apply agentic architectures and Retrieval Augmented Generation (RAG) to build intelligent context-aware AI systems. Experience with Parameter Efficient Fine-Tuning (PEFT) is a plus.
- Performance & Scalability:
- Optimize and fine-tune models for performance efficiency scalability and accuracy across production workloads.
- Cross-Functional Collaboration:
- Work with business stakeholders and engineering teams to translate complex business problems into scalable and efficient AI-driven solutions.
- Continuous Innovation:
- Stay ahead of emerging trends in AI/ML LLMs and MLOps to continuously enhance solution quality and team capability.
- Customer & Partner Engagement:
- Collaborate directly with customer technical experts and partners (e.g. Google) to design solutions that meet business goals and compliance requirements demonstrating technical and business maturity.
Qualifications
- Advanced hands-on experience in Machine Learning LLMs and MLOps.
- Proven expertise in Google Vertex AI Python and Google CCAI/CES platforms.
- Deep understanding of AI governance AIRB security and responsible AI principles.
- Experience in model evaluation frameworks agentic architectures and RAG pipelines.
- Strong communication and collaboration skills for engaging with cross-functional teams vendors and stakeholders.
- Demonstrated ability to balance innovation with operational rigor in production-grade AI environments.
Job Title: AI/ML Architect Work Location: Hartford CT Duration: Longterm Job Description We are seeking a highly experienced Solution Architect to lead the design and implementation of patient solution systems within a pharmaceutical or life sciences environment. The ideal candidate will have a...
Job Title: AI/ML Architect
Work Location: Hartford CT
Duration: Longterm
Job Description
We are seeking a highly experienced Solution Architect to lead the design and implementation of patient solution systems within a pharmaceutical or life sciences environment. The ideal candidate will have a strong background in Salesforce Marketing TIBCO API integrations and Adobe Experience Manager (AEM).
Key Responsibilities:
We are seeking a Senior AI Architect to lead the design development and governance of cutting-edge AI solutions. This role requires both hands-on technical expertise and strategic leadership-driving innovation while ensuring compliance security and scalability across our AI ecosystem.
Key Responsibilities
- AI Leadership & Strategy:
- Lead our end-to-end AI development-balancing hands-on model design and implementation with guiding and mentoring the broader AI engineering and research teams.
- Architecture Design and Deployment:
- Design build and deploy production-grade machine learning models-including LLMs-on the Google Cloud Platform (Vertex AI) using Python and related frameworks.
- Collaboration & Ecosystem Management:
- Partner closely with internal AI teams Google and other technology vendors to sustain momentum drive innovation and align with evolving best practices.
- Governance Security and AIRB Compliance:
- Own and execute AI governance processes including AI Risk Board (AIRB) reviews data security compliance and ethical AI considerations across all AI initiatives.
- Model Development & Evaluation:
- Design and implement models for Conversational AI leveraging Google CCAI/CES components. Lead model evaluation using robust Eval frameworks and metrics to ensure reliability accuracy and fairness.
- Advanced Architectures:
- Apply agentic architectures and Retrieval Augmented Generation (RAG) to build intelligent context-aware AI systems. Experience with Parameter Efficient Fine-Tuning (PEFT) is a plus.
- Performance & Scalability:
- Optimize and fine-tune models for performance efficiency scalability and accuracy across production workloads.
- Cross-Functional Collaboration:
- Work with business stakeholders and engineering teams to translate complex business problems into scalable and efficient AI-driven solutions.
- Continuous Innovation:
- Stay ahead of emerging trends in AI/ML LLMs and MLOps to continuously enhance solution quality and team capability.
- Customer & Partner Engagement:
- Collaborate directly with customer technical experts and partners (e.g. Google) to design solutions that meet business goals and compliance requirements demonstrating technical and business maturity.
Qualifications
- Advanced hands-on experience in Machine Learning LLMs and MLOps.
- Proven expertise in Google Vertex AI Python and Google CCAI/CES platforms.
- Deep understanding of AI governance AIRB security and responsible AI principles.
- Experience in model evaluation frameworks agentic architectures and RAG pipelines.
- Strong communication and collaboration skills for engaging with cross-functional teams vendors and stakeholders.
- Demonstrated ability to balance innovation with operational rigor in production-grade AI environments.
View more
View less