Director of Engineering - Product Development – Gen AI and Data Solutions

Oracle Cloud Infrastructure (OCI) is a pioneering force in cloud technology, merging the agility of startups with the robustness of an enterprise software leader. Within OCI, the Oracle Generative AI Service team spearheads innovative solutions at the convergence of artificial intelligence and cloud infrastructure. As part of this team, you'll contribute to large-scale cloud solutions utilizing cutting-edge machine learning technologies, aimed at addressing complex global challenges.

Join us to create innovative solutions using top-notch machine learning technologies to solve global challenges. We're looking for an experienced Software Development Engineering Leader (M4) to join our OCI Gen-AI Solutions team for strategic customers. In this role, you'll build and lead a team of Generative AI, Applied Scientists and ML Engineers to translate business and functional requirements into concrete deliverables including the design, development, testing and deployment of highly scalable solutions. You collaborate with applied scientists and product managers to design, develop, and deploy tailored Gen-AI solutions with an emphasis on Large Language Models (LLMs) and Retrieval Augmented Generation (RAG) with Oracle23ai and large OpenSearch clusters.

Career Level - M4

As part of the OCI Gen AI and Data Solutions for strategic customers team, you will be responsible for developing innovative Gen AI and data services for our strategic customers. As the first line manager, responsible for tactical direction of staff, negotiating resources, manage subordinates and workloads and setting of schedules, you'll lead the development of advanced Gen AI solutions using the latest ML technologies combined with Oracle's cloud expertise. Your work will significantly impact sectors like financial services, telecom, healthcare, and code generation by creating distributed, scalable, high-performance solutions for strategic customers.

• Work directly with key customers and accompany them on their Gen AI journey – understanding their requirements, help them envision and design and build the right solutions and work together with their ML engineering to remove blockers.
• Collaborate with business stakeholders to ensure Gen AI and ML solutions successfully deliver the business outcomes.
• High visibility opportunity to drive significant business impact, deep-dive into large-scale problem & enable measurable actions via experiments.
• Lead proof-of-value and quantify business impact.
• Lead the team to solve difficult problems, create success & impact for customers. Ensure results and retention of the team conducting regular 1x1s, team meetings, providing feedback, coaching & delegation. Provide thought leadership to scientists and engineers to help invent and implement scalable models while building tools
• Collaborate with cross-functional teams to align Gen AI projects with organizational goals and strategies.
• Build re-usable solution patterns and reference solutions / showcases that can apply across multiple customers.
• Be our product evangelist - engage directly with customers and partners, participate and present in external events and conferences, etc.
• Seek, give and receive critical feedback including but not limited to code review. Strong Program Management and Project Management to multi-task effectively, combined with strong communication with team members, stakeholders and senior management

Qualifications and experience

• Bachelors or master’s in computer science engineering, Mathematics or equivalent technical field with 12+ years of experience 
• 10+ years of professional experience in Cloud Solutions Engineering preferably in a multinational organization.
• Multiple years of experience leading and developing solutions engineering program focused teams 
• Able to optimally communicate technical ideas verbally and in writing (technical proposals, design specs, architecture diagrams and presentations).
• Demonstrated experience in designing and implementing scalable AI models and solutions for production, relevant professional experience as end-to-end solutions engineer or architect (data engineering, data science and ML engineering is a plus), with evidence of close collaborations with PM and Dev teams.
• Ability to collect, organize, and display data in consumable format
• Experience with OpenSearch, Vector databases, PostgreSQL and Kafka Streaming.
• Practical experience with setting up and finetuning large OpenSearch Clusters.
• Experience in setting up data ingestion pipelines with OpenSearch.
• Experience with search algorithms, indexing, optimizing latency and response times.
• Practical experience with the latest technologies in LLM and generative AI, such as parameter-efficient fine-tuning, instruction fine-tuning, and advanced prompt engineering techniques like Tree-of-Thoughts.
• Hands-on experience with emerging LLM frameworks and plugins, such as LangChain, LlamaIndex, VectorStores and Retrievers, LLM Cache, LLMOps (MLFlow), LMQL, Guidance, etc.
• Strong publication record, including as a lead author or reviewer, in top-tier journals or conferences.
• Ability and passion to mentor and develop junior machine learning engineers.
• Excellent verbal and written communication skills
• Embrace and adopt to quick changes

Preferred Qualifications:

• Ph.D. degree or Master’s degree or equivalent experience in computer science, artificial intelligence, machine learning, operations research, or related technical field with 10 years experience
• Experience with RAG based solutions architecture. Familiarity in OpenSearch and Vector stores as a knowledge store
• Knowledge of LLM and experience delivering, Generative AI And Agent models are a significant plus.
• Familiarity and experience with the latest advancements in computer vision and multimodal modeling is a plus.
• Experience with semantic search, multi-modal search and conversational search.
• Experience in working on a public cloud environment, and in-depth knowledge of IaaS/PaaS industry and competitive capabilities. Experience with popular model training and serving frameworks like KServe, KubeFlow, Triton etc.
• Experience with LLM fine-tuning, especially the latest parameter efficient fine-tuning technologies and multi-task serving technologies.
• Deep technical understanding of Machine Learning, Deep Learning architectures like Transformers, training methods, and optimizers.
• Experience with deep learning frameworks (such as PyTorch, JAX, or TensorFlow) and deep learning architectures (especially Transformers).
• Experience in diagnosing, fixing, and resolving issues in AI model training and serving.

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