Director, Action; NBA Platform

Position: Director, Next Best Action (NBA) Platform

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The Director, Next Best Action (NBA) Platform, is accountable for architecting and expanding an enterprise-level, real-time decisioning platform that enables personalized, compliant, and measurable interactions across digital, call‑center, and marketing channels. This position provides both technical and delivery leadership in the areas of decisioning, state management, business rules, machine learning integration, and channel activation, ensuring that all decisions are rapid, transparent, governed, and continuously optimized.

Primary

Responsibilities Platform & Architecture Leadership

• Oversee the comprehensive architecture of real-time decisioning, including:
• Decision orchestration services
• State management and lifecycle tracking
• Eligibility and policy evaluation
• Action and offer metadata management
• Integration of ML scoring and ranking
• Define clear boundaries between decisioning, state management, rules, models, data platforms, and channel systems.
• Ensure the platform operates with low latency, is highly scalable, fault‑tolerant, and fully auditable.

Engineering & Delivery Leadership

• Guide multiple cross‑functional engineering teams responsible for:
• Decision APIs and orchestration services
• State machines and transactional outbox implementations
• Action/offer catalog services
• Rules and policy evaluation services
• Integration of machine learning inference
• Establish engineering best practices related to:
• API contracts
• Idempotency and exactly‑once processing
• Observability, logging, and tracing
• Reliability and performance SLAs
• Drive predictable, agile delivery while maintaining architectural integrity.

Decision Intelligence & Machine Learning Integration

• Collaborate with Data Science and ML teams to:
• Deploy propensity, uplift, and engagement models into production
• Maintain separation between offline modeling and online inference
• Implement safe rollout, monitoring, and fallback strategies
• Ensure explainability and governance of model outputs, particularly in regulated contexts

Experience & Activation Enablement

• Partner with channel and experience teams to ensure decision outputs are:
• Channel‑agnostic
• Rendered consistently
• Enhanced post‑decision without adding latency
• Reusable across web, mobile, call‑center, and marketing platforms

Governance, Compliance & Trust

• Guarantee all decision outputs are:
• Traceable (including rationale and input data)
• Reproducible
• Aligned with regulatory and compliance obligations
• Work with compliance, legal, and audit teams to establish guardrails and controls
• Promote a culture of “decision trust” throughout the organization

People & Leadership

• Build, mentor, and retain senior engineering and architecture talent
• Define clear ownership models and accountability across teams
• Foster an engineering culture centered on clarity, accountability, and results
• Serve as the primary accountable leader for the NBA platform’s technical delivery

Use your skills to make an impact

Required Qualifications

• Minimum 12 years’ experience in software engineering, platform engineering, or distributed systems
• At least 5 years managing large, multi‑team engineering organizations
• Deep expertise in:
• Real‑time APIs and microservices
• Distributed state management
• Event‑driven architectures
• Transactional consistency (e.g., outbox, idempotency)
• Experience with:
• Rules/policy engines
• Machine learning inference in production
• Demonstrated capability to operate in regulated industries (healthcare, finance, insurance, etc.)

Preferred Qualifications

• Experience with personalization, recommendation, or decisioning platforms
• Familiarity with marketing, care navigation, or customer engagement systems
• Experience with enterprise data platforms and feature stores
  
  Excellent executive communication skills, with the ability to clearly explain complex systems

Success Criteria

• Decisions are made rapidly, consistently, and transparently across all channels
• Engineering teams deliver reliably and maintain architectural discipline
• Business stakeholders trust and rely on platform outputs
• The organization can confidently answer “why was this recommended?”
• The platform is continuously refined based on feedback and learning

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