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Principal AI Architect

Principal AI Architect

WabtecIndia
5 hours ago
Job description

How will you make a difference?

We are seeking a collaborative and highly motivated Principal AI Architect to lead our AI team, drive innovation, and enhance customer experiences through impactful artificial intelligence solutions. As a member of the Wabtec IT Data & Analytics (DnA) Team, you will be responsible for :

  • Providing strategic leadership and direction in the development, articulation and implementation, of a comprehensive AI / ML / Data Transformation Roadmap for Wabtec aligned with the overall business objectives.
  • Working with other AI champions in Wabtec evaluating AI tools / technologies / frameworks, champion adoption in different projects and demonstrate value for business and customers.
  • Actively collaborating with various stakeholders to align AI initiatives in Cloud Computing environments (e.g., AWS, Azure, OCI) with business goals.
  • Providing technical oversight on AI projects to drive performance output to meet KPI metrics in Productivity and Quality.
  • Serving as contact and interface with external partners and industry leaders for collaborations in AI / LLM / Generative AI.
  • Architecting and deploying scalable AI solutions that integrate seamlessly with existing business and IT infrastructure.
  • Design and architect AI as a service, to enable collaboration btw multiple teams in delivering AI solutions
  • Optimizing state-of-the-art algorithms in distributed environments
  • Create clear and concise communications / recommendations for senior leadership review related to AI strategic business plans and initiatives.
  • Staying abreast of advancements in AI, machine learning, and data science to continuously innovate and improve solutions and bring the external best practices for adoption in Wabtec
  • Implementing best practices for AI designing, testing, deployment, and maintenance
  • Diving deep into complex business problems and immerse yourself in Wabtec data & outcomes.
  • Mentoring a team of data scientists, fostering growth and performance.
  • Developing AI governance frameworks with ethical AI practices and ensuring compliance with data protection regulations and ensuring responsible AI development.

What do we want to know about you?

You must have :

The minimum qualifications for this role include :

  • Ph.D., M.S., or Bachelor's degree in Statistics, Machine Learning, Operations Research, Computer Science, Economics, or a related quantitative field
  • 5+ years of experience developing and supporting AI products in a production environment with 12+ years of proven relevant experience
  • 8+ years of experience managing and leading data science teams initiatives at enterprise level
  • Profound knowledge of modern AI and Generative AI technologies
  • Extensive experience in designing, implementing, and maintaining AI systems
  • End-to-end expertise in AI / ML project lifecycle, from conception to large-scale production deployment
  • Proven track record as an Architect with cloud computing environments (e.g., AWS, Azure, OCI) and distributed computing platforms, including containerized deployments using technologies such as Amazon EKS (Elastic Kubernetes Service)
  • Expertise with Hands-On experience into Python, AWS AI tech-stack (Bedrock Services, Foundation models, Textract, Kendra, Knowledge Bases, Guard rails, Agents etc.), ML Flow, Image Processing, NLP / Deep Learning, PyTorch / TensorFlow, LLMs integration with applications.
  • Preferred qualifications for this role include :

  • Proven track record in building and leading high-performance AI teams, with expertise in hiring, coaching, and developing engineering leaders, data scientists, and ML engineers
  • Demonstrated ability to align team vision with strategic business goals, driving impactful outcomes across complex product suites for diverse, global customers
  • Strong stakeholder management skills, adept at influencing and unifying cross-functional teams to achieve successful project outcomes
  • Extensive hands-on experience with enterprise-level Python development, PyData stack, Big Data technologies, and machine learning model deployment at scale
  • Proficiency in cutting-edge AI technologies, including generative AI, open-source frameworks, and third-party solutions (e.g., OpenAI)
  • Mastery of data science infrastructure and tools, including code versioning (Git), containerization (Docker), and modern AI / ML tech stacks
  • Preferred : AWS with AWS AI services.
  • We would love it if you had :

  • Fluent with experimental design and the ability to identify, compute and validate the appropriate metrics to measure success
  • Demonstrated success working in a highly collaborative technical environment (e.g., code sharing, using revision control, contributing to team discussions / workshops, and collaborative documentation)
  • Passion and aptitude for turning complex business problems into concrete hypotheses that can be answered through rigorous data analysis and experimentation
  • Deep expertise in analytical storytelling and stellar communications skills
  • Demonstrated success mentoring junior teammates & helping develop peers
  • What will your typical day look like?

  • Stakeholder Engagement : Collaborate with our Internal stakeholders to understand their needs, update on a specific project progress, and align our AI initiatives with business goals.
  • Use Generative AI and machine learning techniques and build LLM Models & fine-tuning, Image processing, NLP, model integration with new / existing applications, and improve model performance / accuracy along with cost effective solutions.
  • Support AI Team : Guide and mentor the AI team, resolving technical issues and provide suggestions.
  • Reporting & Strategy : Generate and present reports to senior leadership, develop strategic insights, and stay updated on industry trends.
  • Building AI roadmap for Wabtec and discussion with senior leadership
  • Training, Development & Compliance : Organize training sessions, manage resources efficiently, ensure data accuracy, security, and compliance with best practices.
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