VP – Product Development

Job Title

Job Description

Key Responsibilities

• Full-stack platform modernization & automation – Leads the end-to-end transformation of a complex cloud-based software platform. This includes migrating a legacy monolithic Python “panel” system to a microservices architecture in Python, developing a robust AWS-centric distributed system, and embedding generative AI capabilities for multi-modal inputs/outputs. The role’s remit spans from UI framework adoption (design system-driven React frontend) to backend service overhaul and establishing AI-driven development processes for rapid, high-quality software delivery.
• Broad cross-functional leadership – Oversees an engineering team that spans frontend, backend, DevOps, and AI/ML. The role works to ensure a cohesive architecture and engineering standards. It involves collaborating closely with portfolio advisors to get a deep understanding of underlying “customer” needs and managing the roadmap. In essence, this leader orchestrates efforts across all layers of the stack and aligns internal and external stakeholders to deliver an integrated, next-generation platform.
• AWS Cloud & Microservices backbone – The platform comprises a ReactJS front-end built on a shared design system, and a Python-based microservices backend (transitioning from older “Panels” infrastructure to Python services). Services are stateless and communicate via a message bus (event-driven, asynchronous communications). Data persistence uses AWS RDS (MySQL) for transactional data and object storage (e.g. S3) for unstructured content. The architecture supports multi-modal capabilities, incorporating generative AI components and external system integrations through a robust API layer.
• Robust data architecture & integration – Responsible for designing and governing the data layer to ensure reliability and performance. This includes optimizing relational schemas (MySQL) for business data and managing object stores for large or unstructured data (images, documents, model outputs). The role ensures data flows seamlessly between internal microservices and external systems through secure APIs, and that multi-modal data (text, voice, image) is properly handled. It also involves maintaining data quality, consistency, and compliance, especially as generative AI models produce or consume data.
• Strategic architecture with deep DevOps integration – The role has a strong emphasis on architectural design (domain-driven microservice boundaries, API strategy, tech stack selection) paired with heavy focus on operational excellence. The leader is accountable for implementing full CI/CD automation, rigorous observability (including cost/financial monitoring, security, performance metrics, and automated alerts), and ensuring high availability. In short, this position balances visionary architecture leadership with hands-on operational rigor to achieve a scalable, resilient platform. Extensive multi-domain expertise – Requires broad and deep knowledge across the entire tech stack: modern web UI development (React, design systems), Python service development, cloud infrastructure (AWS services, containerization, networking), and event-driven microservices (message queues, stateless processing). The individual must also be versed in AI/ML integration, especially generative AI applications (e.g., understanding of LLMs and multi-modal frameworks) to guide how AI features and agent-based automation are built. This depth enables effective decision-making on tooling, frameworks, and design trade-offs in each area of the platform.
• Visionary leadership with strong technical acumen – Predominantly a leadership and strategy role, setting technical direction and nurturing an “AI-native” engineering culture. However, it demands high technical credibility and hands-on understanding: the leader should be capable of reviewing complex code or architecture, quickly prototyping solutions, and validating AI-generated outputs when needed. In practice, the role is about empowering both human engineers and AI agents, guiding design decisions, and stepping in to resolve critical technical challenges or refine approaches drawn from automated development tools.
• AI-augmented engineering & platform innovation – Uniquely focuses on marrying cutting-edge cloud architecture with generative AI-driven development. This role stands out for pioneering an agent-native software development model (experience with Claude Code): orchestrating AI agents to handle coding, testing, documentation, and monitoring, while humans provide oversight and domain context. The leader’s hallmark is driving unprecedented automation and scale in both the platform’s capabilities (multi-modal, intelligent features) and its delivery process (fully automated CI/CD & observability with minimal manual intervention).

Qualifications

• Blackstone seeks to hire individuals who work well in a team-driven working group, are highly motivated, intelligent, have sound judgment and have demonstrated excellence in prior endeavors.
• Deep Technical Expertise in Modern Cloud & Software Stack: Mastery of cloud-native architectures on AWS, including microservices design, containerization, event-driven systems, and distributed computing. Fluent in full-stack development (React frontends with design systems, Python backends) and capable of discerning appropriate technologies for robust APIs, message buses, and data stores.
• Architectural Vision & Domain-Driven Design Judgment: Proven ability to craft and evolve large-scale architectures. Strong knowledge of system design principles, domain-driven design (DDD) for microservices, and strategic migration of legacy systems to modern frameworks. Capable of making high-impact architectural decisions (e.g. service boundaries, data modeling, integration patterns) that balance long-term scalability with immediate needs.
• AI/Agent Orchestration & Integration: Familiarity with generative AI technologies (LLMs, multi-modal models) and how to leverage them in software products and development processes. Skilled at prompt engineering and orchestrating multiple AI agents for tasks like code generation, testing, documentation, and user-facing features. Able to integrate AI capabilities safely into the platform and coordinate human-machine workflows for maximum efficiency and quality.
• Platform Engineering & DevOps Automation: Expertise in building highly automated CI/CD pipelines, infrastructure as code, and comprehensive observability frameworks (monitoring systems for performance, security, cost, and reliability). Ability to ensure that both software delivery and runtime operations are fully automated, repeatable, and resilient, enabling rapid iteration and dependable releases with minimal manual intervention.
• Operating Model Leadership in an AI-Native Environment: Demonstrated skill in leading and evolving a hybrid team where engineers work alongside AI agents. Capable of redefining traditional development processes, fostering an innovative culture where human teams provide strategy and oversight while delegating routine or generative tasks to AI. Strong coaching abilities to help team members adapt to and effectively use AI tools, and to maintain productivity and morale in a novel agent-driven workflow.
• Governance & Compliance Oversight: Ability to establish governance frameworks around AI-augmented software development, ensuring that automated processes produce code and systems that meet quality standards, security policies, and regulatory requirements. This includes setting coding standards, data handling guidelines, and validation checkpoints to keep AI-generated outputs aligned with business and compliance needs.
• Risk Management & Quality Assurance: Experience in identifying and mitigating risks associated with highly automated, AI-integrated systems. This includes managing technical risk (ensuring system reliability, performance, and fail-safes for critical services) and AI-specific risks (like model inaccuracies, misuse of AI, or data leaks). The leader must implement robust QA practices (e.g. automated testing, human-in-the-loop reviews for AI outputs) and maintain contingency plans to swiftly address any issues arising from the new technology or processes.
• Blackstone is committed to providing equal employment opportunities to all employees and applicants for employment without regard to race, color, creed, religion, sex, pregnancy, national origin, ancestry, citizenship status, age, marital or partnership status, sexual orientation, gender identity or expression, disability, genetic predisposition, a or military status, status as a victim of domestic violence, a sex offense or stalking, or any other class or status in accordance with applicable federal, state and local laws. This policy applies to all terms and conditions of employment, including but not limited to hiring, placement, promotion, termination, transfer, leave of absence, compensation, and training. All Blackstone employees, including but not limited to recruiting personnel and hiring managers, are required to abide by this policy.
• The duties and responsibilities described here are not exhaustive and additional assignments, duties, or responsibilities may be required of this position. Assignments, duties, and responsibilities may be changed at any time, with or without notice, by Blackstone in its sole discretion.
• Blackstone is committed to providing equal employment opportunities to all employees and applicants for employment without regard to race, color, creed, religion, sex, pregnancy, national origin, ancestry, citizenship status, age, marital or partnership status, sexual orientation, gender identity or expression, disability, genetic predisposition, veteran or military status, status as a victim of domestic violence, a sex offense or stalking, or any other class or status in accordance with applicable federal, state and local laws. This policy applies to all terms and conditions of employment, including but not limited to hiring, placement, promotion, termination, transfer, leave of absence, compensation, and training. All Blackstone employees, including but not limited to recruiting personnel and hiring managers, are required to abide by this policy.
• If you need a reasonable accommodation to complete your application, please contact Human Resources at 212-583-5000 (US), +44 (0)20 7451 4000 (EMEA) or +852 3656 8600 (APAC).
• Depending on the position, you may be required to obtain certain securities licenses if you are in a client facing role and/or if you are engaged in the following:
• Attending client meetings where you are discussing Blackstone products and/or and client questions;
• Marketing Blackstone funds to new or existing clients;
• Supervising or training securities licensed employees;
• Structuring or creating Blackstone funds/products; and
• Advising on marketing plans prepared by a sales team or developing and/or contributing information for marketing materials.
• Note: The above list is not the exhaustive list of activities requiring securities licenses and there may be roles that require review on a case-by-case basis. Please speak with your Blackstone Recruiting contact with any questions. To submit your application please complete the form below. Fields marked with a red asterisk * must be completed to be considered for employment (although some can be answered "prefer not to say"). Failure to provide this information may compromise the follow-up of your application. When you have finished click Submit at the bottom of this form.