Senior Software Engineering Manager

Wells Fargo

. Lead engineering teams responsible for Digital Experience Protection platforms, services, APIs, detection capabilities, and integrations .

Posted 11/4/2026full-timeUnited StatesSenior💰 $159,000 - $305,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates extensive experience in leading engineering teams focused on Digital Experience Protection, with a strong emphasis on architectural design, AI integration, and production system management. Proven ability to communicate complex technical topics effectively and influence strategic decisions across various stakeholders.

Highest-signal resume keywords

Software Engineering ExperienceManagement ExperienceArchitectural Decision-MakingProduction Incident ManagementBot Management Experience

ATS Keywords

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Hard Skills

API DesignDistributed SystemsScalabilityResiliencySecurityObservabilityAI Solutions DevelopmentBehavioral Signals AnalysisRisk ScoringFraud Detection

Soft Skills

Stakeholder ManagementEffective CommunicationTeam DevelopmentCross-TrainingKnowledge Sharing

Tools & Technologies

Arkose LabsAkamai Bot ManagerBehavioral BiometricsAnomaly Detection PlatformsLLMsAI Agents

Industry Keywords

Digital Experience ProtectionApplication SecurityFraud ControlsCredential AttacksAutomated Threats

Tech Stack

Tools & technologies

Cyber SecurityDistributed Systems

About the role

Key responsibilities & impact

Lead engineering teams responsible for Digital Experience Protection platforms, services, APIs, detection capabilities, and integrations
Establish technical strategy aligned with business needs, customer experience, and evolving threats
Lead architecture and design reviews covering scalability, resiliency, security, latency, observability, and maintainability
Review implementations, APIs, detection logic, and AI-enabled solutions
Guide modular, API-first architectures integrating signals, models, rules, vendors, and internal capabilities
Modernize legacy and vendor-dependent capabilities while maintaining production stability and protection effectiveness
Lead detection strategy for bots, scripted automation, credential attacks, account abuse, automated fraud, and machine-driven threats
Guide layered detection using network, device, behavioral, identity, account, transaction, and historical risk signals
Partner across fraud, cybersecurity, authentication, digital product, architecture, infrastructure, and application engineering
Lead development of AI- and LLM-based detection solutions
Guide production AI architecture, including model integration, grounding, tool calling, evaluation, observability, security, reliability, latency, and deterministic controls
Establish methods to measure AI capability accuracy, explainability, operational performance, and protection value
Prepare DEP for interactions involving humans, automation, software agents, and autonomous AI agents
Recruit, develop, and retain engineers, technical leads, architects, and engineering managers
Establish engineering expectations for code quality, automated testing, deployment safety, observability, vulnerability remediation, documentation, and production ownership
Develop technical leaders and reduce knowledge concentration through ownership, cross-training, reviews, rotations, documentation, and succession planning
Balance delivery with modernization, reliability, technical debt reduction, and capability development
Own performance, availability, resiliency, and engineering health of DEP capabilities
Drive monitoring, capacity planning, resilience testing, incident prevention, root-cause analysis, and operational automation
Establish failure-handling and graceful-degradation strategies
Lead trade-off decisions involving customer experience, protection effectiveness, and platform stability
Ensure incidents and control degradation result in durable improvements
Shape build, buy, and partner strategy for DEP
Evaluate solutions based on effectiveness, signals, explainability, integration flexibility, engineering effort, operational ownership, cost, and time to capability
Influence investment priorities by communicating technical risk, customer impact, threat evolution, and engineering opportunities

Requirements

What you’ll need

7+ years of Software Engineering experience, or equivalent demonstrated through work experience, training, military experience, or education
3+ years of management or leadership experience
5+ years of software-engineering background with ability to participate meaningfully in code, API, architecture, data, AI, and system-design discussions
3+ years designing, modernizing, or operating highly available and high-volume distributed systems
3+ years leading architectural decisions involving scalability, resiliency, latency, security, and observability
3+ years developing engineers and technical leaders and establishing strong engineering practices as a manager or lead technologist
3+ years managing production systems, including production incident management, root-cause analysis, resilience, and continuous improvement
3+ years evaluating technical trade-offs across customer experience, risk, platform stability, cost, and delivery
3+ years communicating complex technical topics effectively to engineers, senior leaders, business, and risk partners; expert stakeholder management
Experience with bot management, application security, digital identity, authentication, fraud controls, or abuse prevention
Knowledge of behavioral signals, device and network intelligence, client telemetry, risk scoring, and decision orchestration
Experience with commercial bot-management technologies such as Arkose Labs, Akamai Bot Manager, or comparable platforms
Experience with behavioral biometrics, anomaly detection, risk engines, or fraud-detection platforms
Experience designing or operating production AI/LLM solutions interpreting behavioral, event, transaction, or telemetry data
Experience combining LLM reasoning with deterministic rules, machine learning, or behavioral analytics
Working knowledge of LLMs, retrieval-augmented generation, model gateways, tool calling, AI agents, evaluation, and AI-assisted engineering
Understanding of adversarial AI and how generative AI and autonomous agents can change automated threats
Experience modernizing high-volume platforms or building internal capabilities that reduce reliance on proprietary technologies
Visa transfer and sponsorship is not available
Ability to provide accurate information and supporting documentation for lawful employment and education verification

Benefits

Comp & perks

Health benefits
401(k) Plan
Paid time off
Disability benefits
Life insurance, critical illness insurance, and accident insurance
Parental leave
Critical caregiving leave
Discounts and savings
Commuter benefits
Tuition reimbursement
Scholarships for dependent children
Adoption reimbursement
Incentive opportunities may be available
Hybrid work schedule