About NovusMinds
NovusMinds is a newly funded startup building AI-native solutions for the wealth management industry. Our WealthOS platform leverages Generative AI, large language models, and intelligent automation to help financial advisors, RIAs, TAMPs, and private banks operate more efficiently and deliver better outcomes for their clients.
We process sensitive financial data, serve enterprise clients with strict uptime expectations, and must scale reliably as we grow. Our AI systems are core to our product, not an afterthought, and we are looking for an engineering leader who treats AI as a first-class discipline.
The Opportunity
This is a rare executive opportunity to define and build the AI engineering function at an early-stage company at the intersection of AI and financial services. As VP of Engineering, AI, you will own the full AI engineering lifecycle, from model development and evaluation through production deployment and monitoring, while building and leading the team that makes it possible.
You will report directly to the CEO and work in close partnership with the CTO, Head of Product, and founding engineers. You will have significant equity, broad executive authority, and the ability to shape the culture and technical direction of the company from day one.
What You Will Do
AI Engineering Leadership & Strategy
• Define and own NovusMinds' AI engineering strategy, setting the technical direction for how we build, evaluate, and deploy LLM-based and Gen AI systems at scale.
• Translate product and business goals into AI system architecture decisions, balancing speed, accuracy, cost, and regulatory compliance.
• Establish engineering standards, design principles, and best practices across model development, evaluation, deployment, and operations.
• Partner with the CEO and CTO to shape the AI product roadmap and advise on emerging AI capabilities, risks, and opportunities relevant to wealth management.
Team Building & People Leadership
• Recruit, hire, and develop a world-class AI engineering team including ML engineers, AI researchers, prompt engineers, and AI reliability engineers.
• Build a high-performance engineering culture grounded in rigor, curiosity, and accountability — where engineers are empowered to solve hard problems and take ownership of outcomes.
• Establish career ladders, performance frameworks, and mentorship structures to retain and grow exceptional AI engineering talent.
• Lead by example: stay technically sharp, participate in code and design reviews, and remain a credible voice in technical discussions.
Model Development & Evaluation
• Architect and oversee the full model lifecycle: data ingestion, fine-tuning, prompt engineering, RAG pipeline design, evaluation, and continuous improvement.
• Build robust evaluation frameworks (evals, red-teaming, regression benchmarks) to ensure AI outputs meet accuracy, safety, and compliance requirements for financial services.
• Drive systematic approaches to model selection, including build vs. buy decisions across frontier models (OpenAI, Anthropic, Google) and open-source alternatives.
• Implement responsible AI practices: hallucination mitigation, output validation, human-in-the-loop workflows, and auditability for regulated use cases.
AI Platform & Infrastructure
• Design and own the AI platform layer: model serving infrastructure, embedding pipelines, vector databases, retrieval systems, orchestration frameworks (LangChain, LlamaIndex, or custom), and inference optimization.
• Collaborate with the Infrastructure Engineer to ensure GPU/compute provisioning, latency targets, and cost efficiency for training and inference workloads.
• Build developer tooling, internal SDKs, and AI platform capabilities that enable the broader engineering team to integrate AI features faster and more reliably.
• Implement observability across all AI systems: prompt/response logging, latency tracking, drift detection, and cost attribution.
Production Reliability & AI Operations
• Own the reliability and uptime of all AI-powered features in production, establishing SLAs, incident response processes, and post-mortem practices specific to AI systems.
• Develop and enforce policies for prompt versioning, model versioning, rollback strategies, and A/B testing of AI features.
• Design systems that degrade gracefully when AI components fail, ensuring enterprise clients experience minimal disruption.
Security, Compliance & Responsible AI
• Ensure all AI systems comply with applicable financial services regulations and data privacy requirements, including careful handling of sensitive client financial data.
• Establish guardrails, content filtering, and PII protection at the AI layer, working with Legal and Compliance to meet SOC 2 and financial services standards.
• Champion responsible AI principles across the organization: transparency, fairness, accountability, and explainability in AI-driven decisions.
What We Are Looking For
Required
• 10+ years of software or ML engineering experience, with at least 3 years in a senior engineering leadership role (Director, VP, or equivalent) managing AI or ML teams.
• Demonstrated track record of shipping AI/ML-powered products to production at scale — not just research or prototyping.
• Deep hands-on expertise with LLMs and Gen AI: prompt engineering, fine-tuning, RAG architectures, evaluation frameworks, and production deployment.
• Experience building and leading high-performing engineering teams: hiring, performance management, culture building, and organizational design.
• Strong proficiency in Python and familiarity with the modern AI/ML stack (PyTorch or JAX, HuggingFace, vector databases, orchestration frameworks).
• Experience with cloud AI infrastructure on AWS (SageMaker, Bedrock) and/or Azure (Azure OpenAI, Azure ML) for training and serving workloads.
• Strong communication skills: able to translate complex AI concepts for non-technical executive and client audiences, and to write clearly about architecture decisions and tradeoffs.
• Genuine passion for AI and its application to real-world enterprise problems, with the intellectual curiosity to stay at the frontier as the field evolves rapidly.
Nice to Have
• Experience in financial services, fintech, or a regulated industry where AI explainability, auditability, and risk management are first-order concerns.
• Background in agentic AI systems: orchestration of multi-step AI workflows, tool-use, and autonomous agent design.
• Familiarity with quantitative finance, wealth management, or financial advisory workflows — or strong appetite to develop domain expertise quickly.
• Prior experience as a founding or early engineering leader at a venture-backed startup, including navigating the chaos and opportunity of building from zero.
• Publications, open-source contributions, or conference presentations in AI/ML.
• Advanced degree (MS or PhD) in Computer Science, Machine Learning, Statistics, or a related field.
Tools & Technologies
LLMs & Gen AI
OpenAI GPT-4o, Anthropic Claude, Google Gemini, Llama, Mistral
Frameworks
LangChain, LlamaIndex, LangGraph, Semantic Kernel, DSPy
ML / Training
PyTorch, HuggingFace Transformers, PEFT / LoRA fine-tuning, RLHF
Vector & Retrieval
Pinecone, Weaviate, pgvector, Qdrant, Azure AI Search
AI Cloud
AWS Bedrock, SageMaker; Azure OpenAI, Azure ML; Vertex AI
Infrastructure
Kubernetes (EKS / AKS), Terraform, Docker, GitHub Actions
Observability
LangSmith, Arize AI, Datadog, Grafana, custom eval pipelines
Languages
Python (primary), TypeScript, SQL, Bash
What We Offer
Executive Equity
Substantial equity package as an executive and founding team member. You will share meaningfully in the company’s success as we scale.
Competitive Salary
Executive base salary benchmarked to Bay Area market rates, reflecting the seniority and scope of this role.
Benefits & Wellness
Full health, dental, and vision coverage. Flexible PTO with a leadership team that models healthy boundaries.
AI-First Culture
Work at the frontier of applied AI. Shape how LLMs enter the $30T+ wealth management market — with resources, autonomy, and a team that takes AI seriously.
Growth & Development
Budget for conferences, research, and continuing education. We expect and support you staying at the cutting edge.
Executive Influence
A seat at the table from day one. Direct access to the CEO, board, and major enterprise clients as you shape both product and company direction.
How to Apply
If you are energized by the challenge of building an AI engineering organization from scratch, defining how large language models and Gen AI enter one of the world’s most consequential industries, and leading a team doing some of the most interesting applied AI work in financial services, we want to hear from you.
NovusMinds is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all team members.