Blackstone Credit & Insurance - AI Engineer, Principal

Responsibilities

• Assessment and Strategy - Assess portfolio companies' technical reality (architecture, data assets, infrastructure, talent), translate findings into strategic insight, contribute to internal memos, and build rapid prototypes to validate proposed strategic moves.
• Tooling and Internal Infrastructure - Build and maintain internal tools that make the team more effective: research automation, assessment templates, tracking systems, and reusable components that accelerate work across the portfolio.
• Partner Evaluation and Execution Oversight - Lead technical diligence on implementation partners, monitor their delivery during active engagements, and participate in working sessions with portfolio company teams alongside the AI Executive.

Requirements

• 5+ years building AI/ML systems in production environments
• Fluency in foundation models, agent frameworks, RAG architectures, vector databases, and evaluation frameworks
• Strong Python engineering skills; experience building APIs and AI-powered applications
• Experience shipping AI-enabled products or features to real users
• Familiarity with cloud infrastructure and production deployment (AWS, GCP, or Azure)
• Proficiency in rapidly assessing unfamiliar technical systems and form defensible architectural views
• Strong written and verbal communication for senior audiences
• Preferred:
• Experience with Model Context Protocol (MCP) or agent-facing API design
• Familiarity with SaaS or enterprise software businesses
• Prior experience in consulting, investing, or technical diligence
• Exposure to private equity, credit, or portfolio operations environments
• No prior financial services experience required.
• 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.
• Expected annual base salary range:
• $215,000 - $250,000

Benefits

Additional Information

Blackstone is the world's largest alternative asset manager. Blackstone seeks to deliver compelling returns for institutional and individual investors by strengthening the companies in which the firm invests. Blackstone's over $1.3 trillion in assets under management include global investment strategies focused on real estate, private equity, credit, infrastructure, life sciences, growth equity, secondaries and hedge funds. Further information is available at www.blackstone.com . Follow @blackstone on LinkedIn , X (Twitter) , and Instagram . Blackstone Credit & Insurance - AI Engineer, Principal Blackstone Credit & Insurance Blackstone Credit & Insurance ("BXCI") is one of the world's leading credit investors. Our investments span the credit markets, including private investment grade, asset-based lending, public investment grade and high yield, sustainable resources, infrastructure debt, collateralized loan obligations, direct lending and opportunistic credit. We seek to generate attractive risk-adjusted returns for institutional and individual investors by offering companies capital needed to strengthen and grow their businesses. BXCI is also a leading provider of investment management services for insurers, helping those companies better deliver for policyholders through our world-class capabilities in investment grade private credit. Team Overview: Blackstone Credit & Insurance AI ("BXCI AI") identifies and responds to AI-driven disruption risk across the BXCI portfolio. We work directly with portfolio company leadership to assess competitive exposure, identify defensible assets, and develop strategies that reposition businesses for long-term viability. Engagements may involve business model transitions, competitive repositioning, revenue model changes, partnerships, acquisitions, and new channels designed to serve AI agents as customers. Role: This role is the primary technical partner to the BXCI AI Operating team across the full engagement lifecycle - from initial assessment through strategy development, partner selection, and hands-on execution. The right candidate is a builder with strong business instincts: deeply fluent in the modern AI stack and proficiency in forming rapid, defensible opinions about unfamiliar technical systems.

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