Senior Software Engineer, AI Center of excellence Uber’s AI Center of Excellence for Security and Privacy is dedicated to building robust, scalable AI-driven products, engineering standards, and policies that proactively safeguard user data, fortify our security posture, and foster trust through transparent communication and innovation. As a leader on this team, you will: 1\. Shape Strategy: Define and drive the roadmap for AI/ML-powered security and privacy solutions that span user-facing applications, downstream services, and core infrastructure platforms. 2\. Architect & Build: Lead the end-to-end design, development, and deployment of high-impact tools and frameworks that integrate seamlessly across Uber’s ecosystem. 3\. Collaborate & Evangelize: Partner with product, engineering, legal, and policy teams to translate complex security and privacy requirements into practical AI solutions—and champion best practices across the organization. 4\. Mentor & Grow: Coach engineers and data scientists in secure ML development, threat modeling, and privacy-preserving techniques, helping to elevate the team’s technical expertise. Basic Qualifications 1\. End-to-End AI/ML & GenAI Expertise: Proven track record designing, developing, and deploying production-quality AI/ML solutions—especially generative AI systems—spanning data ingestion, prompt engineering, model fine-tuning, retrieval-augmented generation (RAG), and inference optimization. 2\. Large Language Model Proficiency: Hands-on experience with foundation models (e.g., GPT, PaLM, LLaMA) and open-source alternatives; adept at prompt design, chain-of-thought engineering, embedding creation, and custom fine-tuning workflows. 3\. Agent Development & Orchestration: Experience building and deploying AI agents—designing multi-step workflows, tool integrations, and autonomous decision-making pipelines to solve complex tasks and drive business value. 4\. GenAI Infrastructure & MLOps: Familiarity with MLOps pipelines for GenAI (model versioning, CI/CD, monitoring, A/B testing), container orchestration (Docker/Kubernetes), and scalable deployment of LLMs in cloud or on-prem environments. 5\. Data & Vector Store Management: Ability to build and maintain scalable data pipelines and vector databases (e.g., FAISS, Pinecone, Weaviate) for efficient semantic search and knowledge retrieval. 6\. Robust Software Engineering: Strong coding skills in Python (and/or Java, Go) with experience in ML frameworks (TensorFlow, PyTorch, scikit-learn) and building secure, maintainable APIs and microservices. Preferred Qualifications 1\. LLM Fine-Tuning Expertise: Hands-on experience fine-tuning large language models using techniques such as LoRA, PEFT, or full-parameter updates on both open-source and proprietary models. 2\. Agent Frameworks: Prior work building or extending agent frameworks (e.g., LangChain, LlamaIndex, or custom in-house solutions) for multi-step reasoning and tool orchestration. 3\. Prompt Engineering Mastery: Deep familiarity with prompt templating, few-shot/zero-shot strategies, chain-of-thought prompting, and mitigation of prompt drift or hallucinations. 4\. GenAI Evaluation & Testing: Experience designing evaluation protocols for generative models (automated metrics and human-in-the-loop testing), with an emphasis on security, bias detection, and reliability. What the Candidate Will Do 1\. Define & Drive AI Security/Privacy Solutions: Architect and implement end-to-end GenAI and ML systems—agents, RAG pipelines, fine-tuned LLMs, and custom models—that proactively detect and mitigate security threats and privacy risks. 2\. Build & Operate Platforms: Develop scalable data pipelines, vector stores, and MLOps infrastructure (CI/CD, monitoring, model-versioning) to support continuous delivery of AI-driven security and privacy features. 3\. Integrate with Uber Ecosystem: Embed AI capabilities into user-facing products, downstream services, and core infrastructure tools—designing APIs, microservices, and tooling for seamless adoption by engineering teams. 4\. Collaborate Cross-Functionally: Partner closely with Product, Legal, Policy, and Security Operations to translate requirements into technical specs, ensure compliance with data-privacy regulations, and align on risk-mitigation strategies. 5\. Develop & Maintain Agents: Build autonomous AI agents and orchestration workflows that interface with internal systems and external tools, automating complex security and privacy tasks. Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuelds progress. What moves us, moves the world - let’s move it forward, together. Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role. \*Accommodations may be available based on religious and/or medical conditions, or as required by applicable law. To request an accommodation, please reach out to [accommodations@uber.com](mailto:accommodations@uber.com).