Job Summary

Senior AI Architect, will be responsible for designing, developing, and deploying advanced AI solutions across a variety of business domains. This role will work on projects that include Generative AI, document and voice intelligence, predictive maintenance, and Agentic AI. This is a hands-on, technical role where you'll be building end-to-end AI systems that are both powerful and scalable, ensuring they solve real-world business problems with a focus on autonomy, efficiency, and innovation. You will leverage your expertise in machine learning, deep learning, and AI system architecture to create intelligent systems capable of making autonomous decisions, improving business processes, and optimizing operations. You will also collaborate across multiple teams to integrate these solutions into broader business workflows.

Responsibilities (Specific tasks, duties, essential functions of the job)

• Advanced AI Architecture and Development:
  • Architect and build end-to-end AI solutions, focusing on machine learning (ML) and deep learning (DL) models, ensuring compliance with data privacy and security best practices when handling sensitive data.
  • Integrate privacy-preserving techniques such as differential privacy in model development to protect user information during training without compromising model performance.
• Generative AI and Deep Learning Expertise:
  • Develop and deploy advanced Generative AI models (e.g., transformers, GANs) for business applications, ensuring that the models adhere to security guidelines to prevent vulnerabilities like data poisoning or adversarial attacks.
  • Implement secure practices in Synthetic Data Generation, ensuring models can be trained on non-sensitive data when needed, addressing privacy concerns.
• Predictive and Prescriptive Analytics:
  • Build and optimize predictive maintenance models using advanced techniques such as time-series forecasting and anomaly detection, while ensuring sensitive data remains encrypted and handled according to privacy regulations.
  • Design prescriptive analytics solutions that recommend actions to improve efficiency, ensuring that all data processing adheres to internal data security standards.
• Autonomous Systems and Agentic AI:
  • Lead the design of autonomous AI systems (including reinforcement learning and multi-agent systems) with robust security measures to prevent unauthorized access or manipulation of the system’s decision-making process.
  • Ensure compliance with data protection regulations while developing autonomous agents that analyze sensitive business data for decision-making.
• AI-Driven Natural Language Processing (NLP):
  • Innovate in document intelligence and NLP solutions, applying privacy-preserving techniques to ensure that personal data in documents, emails, or voice interactions is not exposed during analysis.
  • Implement secure AI practices for text extraction, semantic search, and document classification to ensure privacy and compliance with data protection standards.
• Voice Intelligence & Conversational AI:
  • Develop Voice AI systems with a focus on secure voice data processing, ensuring that voice interactions are encrypted and that users' privacy is respected in accordance with regulatory guidelines.
• Scalable Cloud and Edge AI Solutions:
  • Architect AI systems for deployment across cloud and edge environments, ensuring that all data, particularly sensitive business or customer data, is encrypted and securely stored, both at rest and in transit.
  • Ensure data protection protocols are followed during model deployment and maintenance, safeguarding the privacy and integrity of data throughout the lifecycle.
• Cross-Functional Collaboration and AI Strategy:
  • Partner with product, engineering, and legal teams to define AI solutions that align with business goals while adhering to data security and privacy policies, ensuring compliance with relevant laws such as GDPR and CCPA.
  • Advocate for the integration of security-by-design principles in AI solutions, ensuring data used in AI models is handled with care.
• Innovation & Thought Leadership:
  • Stay informed about the latest advancements in AI security and privacy-preserving machine learning techniques, ensuring that emerging threats and privacy concerns are addressed in AI model development.
  • Lead discussions and innovations in AI security, focusing on AI model robustness and securing AI systems from vulnerabilities.
• Mentorship and Team Development:
  • Provide mentorship and leadership to junior team members, ensuring they are trained in best practices for both AI model development and data privacy within the context of machine learning.

Qualifications (Experience and Education)

• Bachelor’s degree in computer science, Data Science, AI, or Mathematics (required); Master’s or Ph.D. in a relevant field is preferred.
• Overall 12+ years of Experience with 8+ years of professional experience in AI/ML, with a strong background in developing and deploying scalable AI systems.
• Expertise in Generative AI models (e.g., GPT, GANs, Mistral), Prompt Engineering, Reinforcement Learning, and other autonomous systems, with an understanding of data privacy and security considerations.
• Experience with AI platforms such as Dataiku, Data robot, Snowflake, Vertex AI etc.
• Experience working with cloud platforms (Azure/GCP) and AI/ML frameworks (e.g., TensorFlow, PyTorch), ensuring secure deployment of AI systems and compliance with data protection regulations.
• Hands-on experience with secure coding practices and data encryption in AI applications, ensuring models meet privacy requirements.
• Proficient in programming languages like Python, with a focus on security in model development and deployment.
• Strong leadership experience, with the ability to guide teams in both technical and data security aspects of AI development.
• Ability to communicate complex AI concepts and data privacy/security considerations to both technical and non-technical stakeholders.
• Excellent collaboration skills, with the ability to work effectively with cross-functional teams, including product, engineering, and business stakeholders.
• Clear and effective communication skills, capable of explaining complex AI concepts to non-technical audiences.

Disclaimer

The above statements are intended to describe the general nature and level of work being performed by people assigned to this classification. They are not intended to be construed as an exhaustive list of all responsibilities, duties and skills required of personnel so classified.