Principal Generative AI Enterprise Architect

Key Skills

Aartificial intelligence, Azure, Continuous Integration & Continuous Delivery - CI/CD, Data science techniques, Databricks, Effective communication skills, Enterprise Architect, Generative AI, Large Language Models - LLMs, Machine learning techniques, MLOps tools, Natural Language Processing (NLP), Natural Language Toolkit - NLTK, spaCy

Job Description

Join a company that is transforming from a traditional industrial company to a contemporary digital industrial business, harnessing the power of data, analytics, cloud, AI/ML (Machine Learning), automation and design thinking. You will help engineer contemporary applications and services, constructing solutions that remain scalable, adaptable and replicable. You will be part of transforming Honeywell's IT organization through the delivery of technology products that will directly impact the company's growth.

Responsible for Enterprise architecture and conceptual design of Analytics projects in line with the Architecture standards and guidelines. This role requires close working relationship with Business and IT leadership, internal customers, Business Alignment Teams, Enterprise Architecture team and IT COE teams. The role would be the leading Enterprise and Solution Architecture for AI/ML platform & solutions, Generative AI, LLMOps and MLOps, Data Enablement, Information and Analytics function, and will report to Sr. Director, Data, Analytics and Emerging Technologies.

Key Responsibilities

• Lead the architecture and enabling technologies strategy for AI/ML Platform & Engineering, Generative AI enablement, Advanced Analytics and MLOps.
• Evangelize and drive alignment on the adoption and realization of the architecture strategy. Partner with the business alignment team and business leaders on all initiatives in the domain
• Provide thought leadership and act as the trusted technical adviser to the business and technology leadership team.
• Lead the development of a Reference as well as Destination Solution and Technical Architecture standards and Usage guidelines for enabling delivery capabilities based on industry trends, innovation, and business drivers.
• Work as part of the Architecture group, as well as the business alignment team to convert business requirements into an architecture blueprint and conceptual design, based on the Architecture standards and usage guidelines.
• Collaborate with data scientists and data engineers to build production-level models and pipelines, including any required preprocessing of input datasets and postprocessing after model inference.
• Work closely with the operations team to change, optimize existing AI/ML processes and help build effective model performance monitoring, LLMOps to proactively identify problems/issues before business impact.
• Partner and effectively communicate with Non-IT / Business users, functional counterparts and stakeholders to understand the underlying business problem, and work with the extended team to define and communicate the right technical solution
• Facilitate product selection as part of Architecture Standards definition. Partner with Business, Business Alignment Team and Solution Delivery teams to select an approach
• Work with Enterprise Architecture Review Board for Architecture Governance across architecture domains.

YOU MUST HAVE

• Bachelors in Computer Science, Data Science or Engineering fields
• Minimum of 10 years of experience in Information Technology field including 6+ years of extensive practical experience and a comprehensive understanding of AI/ML architecture, Data Science, Data Engineering, MLOps, and working within Enterprise Architecture environment.
• 5+ years of experience in building and deploying Machine Learning solutions using various supervised/unsupervised ML algorithms such as Linear/Logistic Regression, Support Vector Machines, (Deep) Neural Networks, Random Forest, etc and hands-on experience with Python programming and statistical packages, and ML libraries such as scikit-learn, Keras, TensorFlow, PyTorch, MXNet, etc and/or natural language processing using NLTK, spaCy, Gensim, etc.
• 4+ years of experience in building IT use cases / solutions especially around AI/ML cognitive services and platforms, Model productionization, ML Ops, CICD Automation, on Cloud/On-prem environments, including hands-on experience with Generative AI and LLM.
• Excellent understanding of Machine Learning techniques and proficiency in feature analysis, algorithm selection and model hyperparameter tuning.

WE VALUE

• Master’s Degree in Computer Science, Data Science or Engineering fields
• Experience of senior executive/leadership engagement
• Exposure to various aspects of architecture practices and frameworks: business, application, data, security, infrastructure and governance
• Solid hands-on experience with NLP/NLG, AI Conversational Agents & Other Generative AI, MLOps, LLMOps, RAGs, VectorDBs, LangChain, LlamaIndex, and Software development lifecycles
• Experience with Azure OpenAI, Azure Databricks, CloudDBs,
• Experience in reviewing and selecting Technical and Applications Architectures solutions.
• Certifications and specializations in AI/ML, LLMs and Cloud platforms.
• Excellent oral, written and presentation communication skills.