Trulioo

Engineering Manager

• Lead and coach a team of engineers across iOS, Android, and Web
• Own mobile and web delivery end to end from discovery through release, including planning, sequencing, risk management, and stakeholder alignment
• Set technical direction for mobile and web architecture, integration patterns, and quality standards
• Partner with Product and UX to shape customer-focused mobile and web experiences aligned with Trulioo's product strategy
• Coordinate across backend, platform, identity, data, and go-to-market teams
• Establish and maintain practices for code quality, automated testing, release readiness, observability, accessibility, and performance
• Leverage AI and emerging technologies to improve productivity, streamline workflows, and identify continuous-improvement opportunities
• Introduce and scale a shared AI-assisted workflow for code review, testing, or documentation
• Ensure responsible, secure, and compliant use of AI tools and correct weak AI output before release
• Report to the Senior Manager, Software Engineering

Account Executive

• Report to the Sales Director
• Own the full sales cycle for new business across the Payments, e-Commerce, Financial Services, and Technology sectors
• Build relationships with key stakeholders and uncover business needs
• Position Trulioo’s solutions across customer onboarding, identity verification, continuous monitoring, risk management, and fraud prevention
• Build and maintain a strong sales pipeline through targeted outbound prospecting, inbound lead conversion, and strategic customer engagement
• Generate at least $400,000 in new pipeline each quarter
• Manage opportunities through the full sales cycle
• Maintain a rolling pipeline of at least four times quota
• Lead product demonstrations tailored to qualified prospects
• Maintain accurate and timely Salesforce records for forecasting and pipeline visibility
• Drive an efficient sales process targeting an average sales cycle of 90 days or less
• Leverage AI and emerging technologies to improve productivity, decision-making, and sales effectiveness
• Convert qualified opportunities into long-term customer relationships

Mid-Market Account Executive

Financial Planning and Analysis

• Lead the annual operating planning process for the assigned business segment
• Manage and refine rolling forecasts
• Analyze monthly and quarterly results against prior periods and budgets
• Break down and escalate major variances with strategic context
• Collaborate with the VP of FP&A on executive and board communications
• Create KPI dashboards, quarterly board materials, and investor updates
• Analyze margin drivers including transaction volumes, pricing structures, and product mix
• Model growth initiatives with leaders in Sales, Product, Operations, and Customer Success
• Build multi-scenario financial models for corporate development, M&A diligence, integration, and strategic expansion
• Define key metrics for unit economics and efficiency
• Establish automated dashboards and maintain accountability across the organization
• Aggregate financial data from diverse sources and improve transactional data flows
• Use LLMs and AI tools to automate reporting pipelines, optimize forecasting models, and flag transaction anomalies

Strategic Financial Analyst

AI Engineer

• Lead enterprise-wide continuous improvement initiatives using Lean, Six Sigma, or similar methodologies
• Map current-state processes across Operations, Customer Success, Compliance, Sales, Finance, and Engineering
• Identify inefficiencies, bottlenecks, risk exposures, and scalability constraints
• Redesign and standardize workflows to improve cycle time, quality, cost efficiency, and compliance
• Establish KPIs and operational dashboards to measure sustained performance improvements
• Build a culture of continuous improvement through workshops, training, and structured problem-solving
• Define and evolve an automation strategy aligned with operational excellence objectives
• Develop and maintain a value-driven roadmap prioritizing initiatives based on ROI, risk reduction, and scalability impact
• Partner with functional leaders to identify automation and process improvement opportunities
• Assess automation feasibility across rules-based, data-intensive, and AI-augmentable workflows
• Develop ROI-driven business cases and present data-backed recommendations to leadership
• Lead concurrent automation initiatives from discovery through deployment
• Oversee delivery teams implementing automation and AI-enabled solutions
• Drive implementation of UiPath, Automation Anywhere, Blue Prism, Celonis, or Power Automate
• Expand capabilities into intelligent document processing, predictive analytics, and agentic AI use cases
• Establish governance standards for automation lifecycle management, documentation, monitoring, and scalability
• Ensure alignment with enterprise architecture, security, and compliance requirements
• Define and track KPIs for efficiency, adoption, cost reduction, SLA adherence, and quality improvements
• Build reporting dashboards and conduct roadmap and value realization reviews with executive stakeholders
• Embed structured intake, prioritization, and governance processes

Continuous Improvement Lead – AI Intelligence Automation

• Report to the Director of Software Engineering
• Design, build, and own agent systems end-to-end from design through production for identity, fraud, risk, and commerce workflows
• Own evaluation harnesses and observability for shipped systems
• Build reliable, steerable, multi-step agent workflows involving planning, execution, outcome observation, iterative improvement, tool use, and human-in-the-loop patterns
• Troubleshoot non-deterministic failures across models, tools, orchestration, and infrastructure
• Work in a compliance-heavy, globally regulated domain emphasizing auditability, correctness, and human oversight
• Set and communicate technical vision to teammates and directed agents
• Use AI and emerging technologies to improve productivity, streamline workflows, enhance decision-making, and identify continuous-improvement opportunities
• Orchestrate AI agents in daily engineering work, verify outputs, and maintain accountability
• Participate in recruiter, hiring manager, technical, and final leadership interviews

Staff Engineer – AI Agentic Team

Customer Success Manager

• Own the partner relationship end to end for a portfolio of active reseller partners
• Serve as the dedicated account manager and single point of contact across partners’ commercial, technical, and executive teams
• Carry and achieve a year-over-year net-new revenue growth target across the portfolio
• Build, review, and progress partner pipelines; run pipeline reviews, remove blockers, and maintain forecast accountability
• Deliver partner sales onboarding and ongoing enablement for KYC, KYB, and AML solutions
• Co-sell with partner representatives to position Trulioo, advance opportunities, and close deals
• Identify and drive upsell opportunities for partners’ existing clients
• Lead recurring and executive QBRs and business reviews
• Partner with Technical Account Management to maintain healthy, current API integrations and resolve technical friction
• Map partner businesses to identify new use cases, product fits, and expansion paths
• Represent partner needs and market feedback to Product, Marketing, and GTM teams
• Deploy AI-enabled best practices for partner-success workflows, account planning, content creation, and knowledge sharing

Senior Partner Success Manager

Revenue Operations

• Build and run demand generation and account-based marketing for net-new mid-market and enterprise acquisition
• Own lifecycle marketing to grow and retain existing accounts
• Partner with customer success and sales on account expansion
• Own funnel targets and funnel hygiene end to end
• Build the day-to-day operating relationship with SDR leadership
• Drive lead scoring, handoff, and account targeting
• Lead the events team and connect event programs to pipeline outcomes
• Hire and structure the growth marketing team
• Leverage AI and emerging technologies to improve productivity and decision-making
• Build and introduce shared AI-enabled workflows for testing, targeting, and campaign construction
• Report to the Head of Marketing
• Collaborate with sales, customer success, RevOps, and finance

Senior Manager, Revenue Marketing

• Report to the Director of Software Engineering
• Design, build, and own agent systems end-to-end from design through production for identity, fraud, risk, and commerce workflows
• Own evaluation harnesses and observability for shipped systems
• Build reliable, steerable, multi-step agent workflows involving planning, execution, outcome observation, iterative improvement, tool use, and human-in-the-loop patterns
• Troubleshoot non-deterministic failures across models, tools, orchestration, and infrastructure
• Work in a compliance-heavy, globally regulated domain emphasizing auditability, correctness, and human oversight
• Set and communicate technical vision to teammates and directed agents
• Leverage AI and emerging technologies to improve productivity, streamline workflows, and identify continuous-improvement opportunities
• Orchestrate AI agents in daily engineering work, verify outputs, and remain accountable for results
• Participate in recruiter, hiring manager, technical, and final leadership interviews as part of the hiring process

Backend Engineer

• Lead the architecture and development of high-throughput, low-latency back-end services for Trulioo’s Document and Biometric Verification platform
• Design and operate distributed, event-driven microservices for real-time identity verification
• Ingest captured documents and biometric data
• Coordinate ML inference and third-party vendor calls
• Return verification decisions at scale across multiple global regions
• Bridge developer-facing APIs, asynchronous processing pipelines, and ML and infrastructure systems
• Design, build, and maintain secure, modular, horizontally scalable microservices
• Own gRPC/Protobuf contracts and REST/OpenAPI external client interfaces, including versioning and backward compatibility
• Build Apache Kafka streaming pipelines with topics, consumers, and stream-processing topologies
• Model and optimize data access across distributed NoSQL databases, search/indexing systems, and caching layers
• Implement durable, multi-step verification workflows using a workflow engine
• Drive sub-second end-to-end verification latency and predictable throughput
• Tune coroutine concurrency, backpressure, and event-driven autoscaling
• Drive technical architecture and mentor engineers
• Collaborate with Machine Learning, Infrastructure, and Product teams
• Deploy computer vision models and vendor integrations into production
• Use AI coding assistants and internal tooling to accelerate design, implementation, testing, and code review
• Apply AI/ML-driven analysis for anomaly detection, log and metrics insight, capacity forecasting, pipeline performance, throughput, and decision logic optimization

Engineering Manager

Mid-Market Account Executive

Strategic Financial Analyst

Continuous Improvement Lead – AI Intelligence Automation

Staff Engineer – AI Agentic Team

Senior Partner Success Manager

Senior Manager, Revenue Marketing

Staff Engineer – AI Agentic Team

Senior Software Engineer – Back-end, Server