Enterprise Ai Architect

at Oracle in Boise, Idaho, United States

Job Description

As a member of the Oracle Cloud Infrastructure(OCI) Enterprise Engineering Content, Search, and AI Services team, responsible for developing, delivering, and supporting major corporate Services and platforms like Oracle.com, Java.com ,my.oracle.com, etc.

As an Enterprise AI Architect, you will craft and steer the adoption and integration of AI, ML, and DevOps practices within complex business domains. You will collaborate with cross-functional teams, including data scientists, data engineers, developers, operations, IT, and business leadership, to align AI strategies with enterprise goals and aspirations.

Responsibilities

Responsibilities

Architectural Leadership:

Provide strategic leadership in designing and implementing scalable and secure AI architectures for the Enterprise.

AI Strategy Development:

Collaborate with executive leadership to develop and refine the AI strategy, ensuring alignment with business goals and industry best practices.

Solution Design and Implementation:

Lead the design and implementation of AI solutions, leveraging cutting-edge technologies and frameworks to address complex business challenges. Influence and establish best practices through solid design decisions, processes, and tools. Set goals and strategies and oversee the deployment of large-scale projects across multiple technologies.

Cross-Functional Collaboration:

Collaborate with cross-functional teams, including data scientists, engineers, and business stakeholders, to ensure seamless integration of AI solutions with existing systems and processes.

Governance and Compliance:

Establish governance frameworks for AI initiatives, ensuring compliance with regulatory standards and industry guidelines.

Scalability and Performance Optimization:

Design scalable solutions optimized for performance and adaptable to evolving business needs.

Emerging Technologies Evaluation:

Stay abreast of emerging AI technologies, assess their potential impact on the enterprise, and make recommendations for adoption by doing rapid prototyping.

Mentorship and Knowledge Sharing:

Provide guidance and mentorship to the AI team, fostering a culture of innovation, collaboration, and continuous learning. Leading contributors individually and as team members, providing direction and mentoring to others.

Security

Lead various Security and Architecture reviews for complex solutions and integrations for the team.

Work closely with security and risk leaders to foresee and overturn risks, such as training data poisoning, AI model theft, and adversarial samples, ensuring ethical AI implementation and restoring trust in AI systems. Remain acquainted with upcoming regulations and map them to best practices.

Rapid Prototyping

Provide rapid prototyping for various concept projects before they can be prioritized, including developing, training, fine-tuning, and deploying large multimodal language models for retrieval augmented generation. Apply instruction tuning, reinforcement learning from human feedback (RLHF), and parameter-efficient fine-tuning such as p-tuning, adaptors, LoRA, and so on to improve LLMs for different domain-specific RAG use cases. Measure and benchmark models and applications performance.

Qualifications

+ Bachelors, Master's, or Ph.D. in Computer Science, Artificial Intelligence, or a related field.

+ 10+ years' proven experience as an Enterprise Architect, Solution Architect, or a similar role, focusing on AI/ML and generative AI in the last 5+ years.

+ 5+ years of hands-on 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, Cloud/On-prem environments,

+ Proficient in programming languages such as Python, R, Java, etc.

+ Experience working with RAG technologies such as LLM frameworks (Langchain and LLamaIndex), LLM model registries (Hugging Face), LLM APIs, embedding models, and vector databases (FAISS and Milvus).

+ Understanding of key libraries used for LLM and RAG development: for NLP models development (e.g., NeMo, DeepSpeed, HuggingFace), for deployment (e.g., TensorRT-LLM, Triton Inference Server) for Information Retrieval (e.g., RAPIDS, Milvus, Pinecone, Open Search).

+ Experience working with larger transformer-based architectures for NLP, CV, ASR, or others.

+ Experience interacting with REST APIs and microservices.

+ Strong understanding of machine learning, deep learning, computer vision, natural language processing concepts, and speech recognition concepts.

+ Deep expertise in cloud-based AI services like OCI Data Science Platform, OCI AI Services, Oracle Digital Assistant, AWS AI Services or Azure AI Services

+ Solid understanding of machine learning principles, including advanced analytics tools, applied mathematics, ML and Deep Learning frameworks and libraries, and ML techniques.

+ Proficient in using Jupyter Notebooks for all sorts of data science tasks such as exploratory data analysis (EDA), data cleaning and transformation, data visualization, statistical modeling, machine learning, and deep learning.

+ Hands-on experience with cloud-based platforms and services, such as OCI, AWS, GCP, and Azure.

+ Proven ability to optimize LLM models for inference speed, memory efficiency, and resource utilization.

+ Experience deploying LLM models in cloud environments (e.g., OCI, AWS, Azure, GCP) and on-premises infrastructure.

+ Familiarity with containerization technologies (e.g., Docker) and orchestration tools (e.g., Kubernetes) for scalable and efficient model deployment.

+ Strong knowledge of GPU cluster architecture and the ability to leverage parallel processing for accelerated model training and inference.

+ Excellent communication skills and the ability to convey complex technical concepts to non-technical stakeholders.

+ Ability to work independently and collaboratively in a fast-paced environment.

+ Practical knowledge of Agile project management and software development methodologies such as Scrum and SAFe.

+ Ability to take feature/design through the software lifecycle to release robust, high-quality production code

+ Experiencing working with globally distributed teams.

Disclaimer:

Certain US customer or client-facing roles may be required to comply with applicable requirements, such as immunization and occupational health mandates.

Range and benefit information provided in this posting are specific to the stated locations only

US: Hiring Range: from $96,800 to $251,600 per annum. May be eligible for bonus, equity, and compensation deferral.

Oracle maintains broad salary ranges for its roles in order to account for variations in knowledge, skills, experience, market conditions and locations, as well as reflect Oracle's differing products, industries and lines of business.

Candidates are typically placed into the range based on the preceding factors as well as internal peer equity.

Oracle US offers a comprehensive benefits package which includes the following:

1. Medical, dental, and vision insurance, including expert medical opinion

2. Short term disability and long term disability

3. Life insurance and AD&D

4. Supp