Gen AI Solutions Product Architect -SVP

Role Overview:  

As the Gen AI Solutions Product Architect, you will drive the development of a modular, reusable Gen AI product suite that enables cross-functional teams to deploy AI solutions rapidly without deep business context. You will architect "plug-and-play" Gen AI modules (e.g., RAG, prompt engineering, text-to-SQL) and foster an open-source-like community for contributions. This role demands a blend of product strategy, technical architecture, and cross-functional collaboration to ensure solutions are scalable, user-friendly, and aligned with enterprise needs.  

Key Responsibilities  

1. Product Roadmap & Modular Design  

   - Define the product vision and roadmap for reusable Gen AI modules (e.g., RAG, prompting frameworks, hybrid ML/LLM systems).  

   - Architect parameterized, business-agnostic solutions that abstract complexity (e.g., pre-configured prompts, vector DB connectors, chunking logic).  

   - Design APIs and microservices to expose modules as reusable components (e.g., “text-to-SQL service,” “RAG-as-a-service”).  

2. Technical Leadership  

   - Standardize patterns (e.g., prompt templates, chunking strategies, few-shot training pipelines) across use cases.  

   - Integrate LLM workflows (e.g., OpenAI, Claude) with traditional ML (clustering, classification) and enterprise systems (databases, UI tools).  

   - Optimize performance of Gen AI components (cost, latency, accuracy) and ensure scalability (e.g., load balancing for vector DBs).  

3. Cross-Functional Collaboration  

   - Partner with business teams to map their needs to pre-built modules (e.g., “Your compliance use case fits our RAG module with these parameters”).  

   - Build developer tools (SDKs, UI templates) to help teams self-serve (e.g., drag-and-drop prompt builders, vector DB configurators).  

   - Foster an open-source-like community: Create contribution guidelines, review external code, and incentivize modular feature additions.  

4. Adoption & Enablement  

   - Develop documentation, tutorials, and sandbox environments for testing modules.  

   - Train teams on best practices (e.g., prompt engineering, security for LLM outputs).  

   - Track metrics: Module reuse rate, contribution volume, time-to-deploy for new use cases.  

Required Skills & Experience  

Technical Expertise  

- Gen AI/ML Engineering:  

  - Hands-on experience with LLM integration (e.g., OpenAI, Anthropic, Llama 2) and frameworks (LangChain, LlamaIndex).  

  - Expertise in RAG workflows: Document chunking (sentence transformers), vector DBs (Pinecone, FAISS), and hybrid search.  

  - Familiarity with text-to-SQL systems, few-shot/chain-of-thought prompting, and traditional ML (clustering with scikit-learn, PyTorch).  

- Software Engineering:  

  - Proficiency in Python, API design (FastAPI, Flask), and cloud platforms (AWS Sagemaker, Azure AI).  

  - Experience with CI/CD, containerization (Docker), and infrastructure-as-code (Terraform).  

- UI/Integration Skills:  

  - Frontend integration (React/Streamlit for config UIs) and middleware (message queues, auth systems like R2D2).  

Product & Strategy  

- Proven track record of building reusable ML/API products or internal platforms.  

- Ability to translate business problems into technical requirements (e.g., “Compliance needs a RAG module with PII redaction”).  

- Agile/Scrum methodology and tools (Jira, GitHub Issues).  

Soft Skills  

- Strong communication to bridge technical and non-technical stakeholders.  

- Community-building skills to drive adoption and contributions.  

- Pragmatic problem-solving (e.g., balancing customization vs. standardization).  

Preferred Qualifications  

- Experience with open-source projects (contributor/maintainer).  

- Knowledge of LLMOps tools (PromptLayer, Weights & Biases).  

- Background in enterprise integration (SSO, RBAC, logging/monitoring).  

Education:

• Bachelor’s/University degree in Computer Science, Data Engineering, Cloud Computing, or a related field, or equivalent experience, potentially Master's degree/MBA

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In addition to salary, Citi’s offerings may also include, for eligible employees, discretionary and formulaic incentive and retention awards. Citi offers competitive employee benefits, including: medical, dental & vision coverage; 401(k); life, accident, and disability insurance; and wellness programs. Citi also offers paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays. For additional information regarding Citi employee benefits, please visit citibenefits.com. Available offerings may vary by jurisdiction, job level, and date of hire.

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