Director, Software Engineering - Agentic AIPlatform Engineering
Financial Services | Regulated Enterprise | Agentic AI
1. Job DescriptionWe are seeking an experienced and visionary Director of Artificial Intelligence to join our Platform Engineering organization. This is a senior leadership role responsible for driving the strategy, design, and delivery of AI-powered capabilities across a large-scale, regulated financial services enterprise. The Director will own the technical and organizational roadmap for our Agentic Software Development Lifecycle (SDLC) Platform - a custom-built, governed AI platform that accelerates developer productivity, automates engineering workflows, and integrates AI agents into the fabric of our software delivery pipeline.
The ideal candidate brings deep hands-on expertise in large language model (LLM) orchestration, agentic AI frameworks, and enterprise-grade infrastructure, combined with the leadership presence and communication skills to influence the CIOs and executive level. You will operate at the intersection of AI innovation and regulatory compliance, ensuring that AI capabilities are delivered safely, responsibly, and in alignment with SOX, OCC, and FFIEC requirements.
2. ResponsibilitiesStrategic Leadership- Define and execute a multi-year AI strategy for Platform Engineering aligned with the firm's technology and business objectives.
- Own the vision and delivery roadmap for the Agentic SDLC Platform, integrating AI agents into code review, requirements generation, test automation, security scanning, and release workflows.
- Partner with CIO, CTO, and line-of-business technology leaders to shape AI adoption priorities and funding.
- Serve as an internal thought leader and evangelist for responsible, regulated AI - translating emerging capabilities into practical, compliant solutions.
Platform Delivery & Engineering- Lead the design, build, and production operation of agentic AI infrastructure built on LangGraph, LangSmith, and Azure (AKS, APIM, Cosmos DB, Service Bus).
- Oversee knowledge store architecture encompassing Neo4j (graph), pgvector (semantic search), and Microsoft Fabric medallion data pipelines.
- Ensure platform security by governing per-resource On-Behalf-Of (OBO) token chains, Attribute-Based Access Control (ABAC), and identity lifecycle across Azure AD App Registrations, Managed Identities, and Service Principals.
- Drive GitHub Enterprise integration patterns including Copilot Cloud Agent, webhook-triggered LangGraph routing, and enterprise-scale API engineering across 16,000+ repositories.
Governance & Compliance- Establish and maintain AI governance frameworks covering model risk, data lineage, audit trails, and agent behavior in accordance with SOX, OCC, and FFIEC standards.
- Define Agent Governance policies (ethical guardrails, explainability, escalation paths) distinct from Agent Operations (runtime monitoring, observability, SLAs).
- Collaborate with Legal, Compliance, and Information Security to conduct AI risk assessments and maintain regulatory posture.
- Evaluate and disposition third-party AI platforms and SaaS vendors against regulated enterprise requirements, maintaining architectural independence where required.
Team Leadership & Talent Development- Hire, develop, and retain a high-performing team of AI engineers, platform architects, and applied ML practitioners.
- Establish engineering standards, code quality practices, and career development frameworks for the AI engineering discipline.
- Foster a culture of experimentation, psychological safety, and continuous learning within a regulated operating environment.
Stakeholder Engagement- Communicate AI strategy, progress, and risks clearly to executive audiences including CIO, Chief Architect, and Board-level committees.
- Produce investment justifications, business cases, and CIO-level briefing materials for AI platform initiatives.
- Manage relationships with strategic technology partners including Microsoft, GitHub, Anthropic, and key cloud vendors.
3. Essential Skills & ExperienceLeadership & Experience- 10+ years of progressive technology leadership experience, with at least 3 years in a director-level or equivalent senior leadership role.
- Demonstrated experience leading AI/ML or platform engineering teams in a large, complex enterprise environment (5,000+ users, 500+ applications).
- Proven track record delivering production AI systems that operate under regulatory or compliance constraints (financial services, healthcare, or similarly regulated industries strongly preferred).
- Experience building and presenting CIO-level business cases, roadmaps, and investment justifications for emerging technology platforms.
Technical Depth - AI & Agentic Systems- Deep expertise in LLM orchestration frameworks, particularly LangGraph and LangChain, including multi-agent workflow design, state management, and tool routing.
- Hands-on experience with agentic AI patterns: agent loops, memory architectures, human-in-the-loop checkpoints, and observability via LangSmith or equivalent.
- Strong understanding of RAG (Retrieval-Augmented Generation) pipelines, vector databases (pgvector, Pinecone, Weaviate), and knowledge graph integration (Neo4j).
- Familiarity with prompt engineering, fine-tuning strategies, and model evaluation at enterprise scale.
Technical Depth - Cloud & Infrastructure- Extensive hands-on experience with Azure Platform services: AKS (Kubernetes), APIM, Cosmos DB, Azure Service Bus, Azure AD, and Managed Identities.
- Proficiency with enterprise data platform architecture, including medallion/lakehouse patterns (Microsoft Fabric or equivalent).
- Strong understanding of GitHub Enterprise ecosystem: GitHub Apps, Actions, Copilot, HMAC-SHA256 webhook security, and large-scale repository management.
- Experience designing and governing identity security architectures - OBO token flows, ABAC policies, App Registrations, and Service Principals.
Governance & Regulatory Knowledge- Working knowledge of SOX IT general controls, OCC guidance on model risk management (SR 11-7), and FFIEC technology examination standards.
- Experience establishing AI governance programs covering model risk, data governance, audit logging, and ethical AI principles.
- Ability to construct and maintain regulatory-grade documentation for AI systems including Architecture Decision Records, risk assessments, and control matrices.
4. Desirable Skills & ExperienceThe following qualifications are not required but will strengthen a candidate's profile:
Advanced AI & Research- Experience with advanced AI evaluation frameworks, red-teaming, and adversarial testing for enterprise LLMs.
- Familiarity with Anthropic Claude APIs (including Claude Mythos Preview / Project Glasswing), OpenAI GPT series, or other frontier model APIs at scale.
- Published research, conference presentations, or patents in AI/ML or agentic systems.
- Exposure to multi-modal AI capabilities (vision, document understanding, code generation) in enterprise workflows.
Platform & Ecosystem- Background in developer experience (DevEx) platforms, internal developer portals, or platform engineering as a product discipline.
Financial Services Domain- Domain knowledge in Wealth Management, Asset Management, Asset Servicing, or Treasury/Cash Management technology stacks.
- Prior experience navigating technology change in organizations subject to OCC model risk examinations or FFIEC cybersecurity assessments.
- Understanding of Snowflake, Databricks, or similar enterprise analytics platforms in regulated data environments.
Leadership & Communication- MBA or graduate degree in Computer Science, Engineering, or a related technical discipline.
- Experience as a principal author of enterprise architecture frameworks, TDDs, or technology strategy white papers.
- Active participation in AI industry forums, standards bodies, or open source AI communities.
This role is based in our Platform Engineering organization. Candidates must be eligible to work in a regulated financial services environment and subject to applicable background screening
Salary Range:
$156,370 - 273,600 USD
Salary range is a good faith estimate of base pay. Northern Trust provides a comprehensive benefits package including retirement benefits (401k and pension), health and welfare benefits (medical, dental, vision, spending accounts and disability), paid time off, parental and caregiver leave, life & accident insurance, and other voluntary and well-being benefits. Northern Trust also provides a discretionary bonus program that may include an equity component.
