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Associate Director - AI Solutions

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Onsite

Associate Director - AI Solutions

Visionet Systems Inc.

Associate Director - AI Solutions

Skills

Google Cloud PlatformSQL QueriesDeep LearningPythonPyTorchTensorFlowMachine LearningAIAWSNLP / Natural Language ProcessingHadoopAzure

1 month ago

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Important information


Contract type:

Freelance / Contract

Location:

New York, NY, USA

Work mode:

Onsite

Published on:

30 September 2026

What they need


AI Portfolio Management

  • As the focal point for all AI initiatives within the IT team, manage a dedicated AI portfolio and consult with the cross-functional IT teams on their AI projects, fostering a cohesive approach to AI development and implementation.

Develop and implement ethical AI solutions

  • Identify and translate complex business challenges into AI solutions.
  • Assess organizational needs, recommend ethical solutions, gather requirements, design and develop AI solutions, and deploy them into production environments within required budget and quality standards expectations.
  • Define project scope, gain insight and agreement from others, allocate resources, manage timelines, and mitigate risks.

AI Strategy

  • Collaborate with the CITO and senior leaders from cross-functional teams on refining the foundation’s AI strategy to ensure that the foundation’s AI systems, guidelines, processes, and procedures are aligned to the foundation’s mission and values and are being scaled throughout the entire foundation.

Governance & policy development

  • Monitor evolving AI regulations and data privacy laws.
  • As a key member of the AI Advisory Group, draft, implement, and maintain clear, accessible Responsible AI guidelines, safety policies, and use-case criteria for the whole foundation to follow.
  • Ensure all AI-related activities, all relevant stakeholders are aware of and adhering to ethical guidelines and protecting organizational data.
  • Promote responsible AI development and deployment within the organization across departments, while considering potential biases, fairness, and transparency in AI systems.

AI Model evaluation and optimization

  • Continuously monitor and evaluate the effectiveness and performance of AI models, identifying areas for improvement and implementing optimization strategies to reduce our carbon footprint and enhance accuracy, efficiency, and scalability.

Vendor & technology assessment

  • Remain up-to-date with emerging AI trends, technologies, and best practices.

  • Research and recommend new AI tools and techniques to improve operational efficiency and drive innovation.

  • Evaluate, propose and manage AI vendors and consultants to deliver strategic value within an approved budget.

  • 8+ years of related professional experience and a Bachelor’s or Master’s degree in Computer Science, AI, Machine Learning, or a related field (or an equivalent combination of education and experience).

Required Skills

  • Proficient in Python and AI frameworks (e.g., TensorFlow, PyTorch), with expertise in machine learning, deep learning, NLP, foundational models, and GenAI technologies.
  • Experienced in Generative AI techniques (e.g., LLMs, LangChain, RAG), Agentic architecture, and establishing connections using Model Context Protocol (MCP).
  • Experience with Google Cloud Platform (GCP), Vertex AI, and production deployment using Gemini Enterprise or equivalent platforms (working knowledge of Google’s ADK is a plus).
  • Familiar with major cloud platforms (AWS, Azure, GCP), data technologies (SQL, Hadoop, Spark), and AI Ops principles (CI/CD pipelines, containerization, automated testing).
  • Experienced in deploying AI models to cloud environments—optimizing for performance, latency, cost, and resource utilization (GPU/TPU)—and troubleshooting issues like performance drift.
  • Strong capability in working with large datasets, extracting meaningful insights from unstructured data, and understanding content management systems, knowledge graphs, and information retrieval techniques.
  • Demonstrated ability to recommend and apply practical AI solutions to real-world problems within content-rich domains.
  • Deep conceptual understanding of how models process data, exhibit bias, and handle data privacy.
  • Excellent project management skills with experience managing complex AI projects using Agile development methodologies.
  • Experience managing AI vendors and the technical capability to evaluate vendor claims regarding model safety, data retention, and training data provenance.
  • Strong communication, interpersonal, and relationship-management skills

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