Sr Director of Software Engineering - AI/ML platforms (Intelligent Agentic Systems, RAG, LLM Architectures)

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Your expertise is applied cross-functionally to drive the adoption and implementation of advanced ML, AI, and intelligent agentic systems within various teams and aid the firm in remaining at the forefront of industry trends, best practices, and technological advances.</p><p><strong>Job Responsibilities</strong></p><ul><li>Lead multiple technology and process implementations across departments to achieve firmwide objectives in machine learning, large language models (LLMs), search, and agentic systems.</li><li>Directly manage strategic initiatives focused on the development, deployment, and monitoring of advanced ML and AI solutions.</li><li>Provide leadership and high-level direction to cross-functional teams, overseeing the end-to-end lifecycle of AI/ML projects from ideation to production.</li><li>Act as the primary interface with senior leaders, stakeholders, and executives, driving consensus and alignment across competing objectives in intelligent operations.</li><li><p style=\"line-height: normal; margin-bottom: 0in;\">Sets and scales multi-department strategy for agentic AI-enabled engineering and SDLC/TLM automation (using enterprise-authorized tools within the work environment) to drive firmwide objectives (speed, scalability, reliability, and cost-to-serve), including portfolio-level standards for AI-orchestrated delivery workflows, release governance, automated test modernization, resilience engineering, and incident response acceleration; establishes guardrails for validation, security, resiliency, traceability, and reuse.</p></li><li><p style=\"line-height: normal; margin-bottom: 0in;\">Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to drive cross-domain reuse and measurable capacity unlock outcomes across departments.</p></li><li>Manage multiple stakeholders, complex projects, and large cross-product collaborations, ensuring best practices in model governance, data privacy, and ethical AI.</li><li>Influence peer leaders and senior stakeholders across business, product, and technology teams to foster innovation and operational excellence.</li><li>Develop high-performing teams of data scientists, ML engineers, and AI researchers.<br>&nbsp;</li></ul><p><strong>Required qualifications, capabilities, and skills</strong></p><ul><li>Formal training or certification on machine learning, artificial intelligence, LLM, search, and agentic systems concepts and 10+ years applied experience. In addition, &nbsp;5+ year &nbsp;of experience leading technologists to manage, anticipate and solve complex technical items within your domain of expertise and more broadly across the organization</li><li>Experience developing or leading large or cross-functional teams of technologists, including data scientists, ML engineers, and AI researchers.</li><li>Demonstrated prior experience influencing across highly matrixed, complex organizations and delivering value at scale.</li><li>Experience leading complex projects supporting system design, testing, and operational stability, including model development, validation, and continuous improvement.</li><li><p style=\"line-height: normal; margin-bottom: 0in;\">Experience leading multi-organization adoption of agentic AI-enabled engineering operating models (using enterprise-authorized tools within the work environment), including defining governance (human-in-the-loop decisioning, quality gates), measurement frameworks, and secure handling of sensitive inputs/outputs across teams.</p></li><li><p style=\"line-height: normal; margin-bottom: 0in;\">Deep understanding of responsible AI risk, controls, and resiliency/security expectations at scale, with demonstrated ability to advise senior leaders on safe adoption, portfolio governance, and reuse-first strategies.</p></li><li>Extensive practical cloud native experience and expertise in ML/AI platforms and MLOps.</li><li>Advanced degree (PhD or Master’s) in Computer Science, Machine Learning, Artificial Intelligence, or related technical field.</li><li><p>Deep expertise in LLM architectures, Retrieval-Augmented Generation (RAG), fine-tuning, and intelligent agentic systems.</p><p>&nbsp;</p></li><li>Outstanding written and verbal communication abilities, with experience preparing and delivering impactful presentations and strategic recommendations.<br>&nbsp;</li></ul><p><strong>Preferred qualifications, capabilities, and skills</strong></p><ul><li>Publications or patents in machine learning, artificial intelligence, or related domains.&nbsp;</li><li>Experience working at code level and with cloud-based ML platforms.</li></ul>",
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