LivePerson

Solutions Engineer

• Develop best-practice configurations and solution designs that meet the technical requirements of each customer’s program or deployment.
• Set up, develop, configure, and test all technical assets according to project scope and timelines. Includes responsibility for LE Tag and taglet code development.
• Collaborate with LivePerson Product and R&D teams to build feature extensions that support brand and customer needs.
• Identify relevant use cases and business needs for LivePerson capabilities, and successfully deploy these enhancements into customer accounts.
• Serve as a subject-matter expert (SME) across the full suite of LivePerson solutions, features, and technical offerings.
• Act as a trusted advisor by guiding customers on how to apply LivePerson technical solutions to achieve their business objectives.
• Manage customer technical assets (APIs, integrations, widgets, code), while continuously expanding and introducing new technical solutions to drive adoption, usage, and value.
• Maintain high levels of customer satisfaction and responsiveness, improving sentiment, reducing attrition, and increasing referenceability.
• Support and lead activities that advance key strategic initiatives through strong technical and solutions leadership.
• Continuously optimize and share best practices and lessons learned to improve program efficiency and outcomes through technical solutions.
• Assist LivePerson partners by providing technical enablement, ensuring they can successfully develop and deploy LivePerson solutions. Act as an SME to drive partner success.

Solution Engineer II

Backend Engineer

• Design and develop high-volume, low-latency applications for mission-critical systems and deliver high-availability and performance
• Design REST-based backend services
• Debug production issues and help maintain existing code
• Development of technical specifications and documentation
• Participate in on-call rotations
• Work with Bots & Automation team in building next-generation bot runtime platform

Java Backend Engineer – SDE II

DevOps Engineer

• Develop and maintain automation solutions using Python, Terraform, Ansible, and Bash to streamline deployment, configuration, and management of infrastructure and applications.
• Collaborate closely with development, operations, and other cross-functional teams to understand project requirements, create automation strategies, and deploy efficient solutions.
• Utilize cloud technologies and services, with a preference for Google Cloud Platform (GCP), to architect and manage scalable, secure, and highly available infrastructure.
• Troubleshoot issues across development, testing, and production environments, ensuring rapid resolution and minimal downtime

Technical Product Manager

• Develop and articulate a clear product vision and strategy for Conversational AI Teams, ensuring alignment with the company's goals and strategic advancements.
• Define, review feature requests, and prioritize product features and enhancements based on customer feedback, market research, competitive analysis, and business objectives, focusing on message processing, real-time routing, and system scalability.
• Create and maintain a detailed product roadmap, outlining key milestones, dependencies, and timelines for delivering new AI capabilities that enhance conversation handling and agent assist features.
• Work closely with Engineering, Infrastructure, Cloud, AI/ML teams, Sales, and Customer Success to align priorities and drive execution of platform improvements that optimize system performance and reliability.
• Champion a platform-first approach, ensuring the Conversational AI platform infrastructure is designed for high availability, low latency, and the ability to process billions of messages with optimal efficiency.
• Conduct ongoing research and analysis to identify emerging trends in large-scale messaging, Conversational AI, AI-driven routing, and emerging LLM trends to inform platform evolution.
• Engage with enterprise customers, partners, and internal stakeholders to gather insights on performance bottlenecks, pain points, and evolving needs, translating feedback into actionable product improvements.
• Partner with Marketing, Sales, and Customer Success teams to develop go-to-market strategies, ensuring seamless adoption of new platform features and driving overall business impact.
• Define key performance indicators (KPIs) and metrics to measure the effectiveness of Conversational AI platform capabilities, leveraging data to optimize performance, reduce latencies, and improve AI routing and resolution accuracy.
• Stay informed about advancements in Conversational AI systems, large language models (LLMs), and best practices in high-scale AI infrastructure, sharing insights to drive platform innovation.

Senior Technical Product Manager – Conversational AI

• Develop and articulate a clear product vision and strategy for our end-to-end Analytics platform, ensuring it empowers customers and internal teams to gain actionable insights from Conversational Data.
• Define, review, and prioritize features for the Analytic Studio/Builder and Report Center, focusing on an intuitive user experience for data exploration, visualization, and report scheduling.
• Manage the product roadmap for Data Services and Data Transporter, guaranteeing the timely, accurate, and scalable ingestion and preparation of petabyte-scale conversational data streams.
• Work closely with Data Science and Engineering teams to integrate Conversational Intelligence (AI/ML-derived insights) features directly into the core analytics products.
• Define and track key performance indicators (KPIs) and data quality metrics for all data pipelines and analytic tools, ensuring high data reliability, freshness, and tool usage.
• Act as the primary interface between Analytics users (internal and external) and the Data Engineering teams, translating complex data requirements into clear, technical specifications.

Senior Technical Product Manager – Analytics

Full-stack Engineer

• Design, develop, and deploy scalable back-end services.
• Build responsive and intuitive front-end user interfaces.
• Collaborate with product managers, designers, and other engineers to define and implement new features.
• Maintain and improve the performance, quality, and responsiveness of existing applications.
• Write clean, well-tested, and maintainable code.
• Troubleshoot, debug, and upgrade existing systems.
• On call rotation

Full Stack Software Developer

• Learn new technologies and architectures, including work with uniform data layers, integrations with contact center providers, and new product development.
• Work with leadership to bring your engineering experience to the table and ideate new features and functionality.
• Design, build, and maintain Python-based backend services that orchestrate AI agent workflows using LangChain and LangGraph.
• Contribute to the development of a multi-tenant simulation platform handling high volumes of concurrent AI-driven conversations in a public cloud environment.
• Integrate with contact center providers (such as LivePerson) and external LLM providers through a unified gateway abstraction.
• Build and extend REST APIs using the Litestar framework, following strong typing and Pydantic-based data modeling patterns.
• Work with Couchbase for conversation state persistence, implementing optimistic concurrency patterns (CAS locking) for correctness in multi-pod deployments.
• Write high-quality, well-tested code with a focus on behavior-driven unit and integration testing.

Software Development Engineer II

Product Designer

• Lead end-to-end design for key product initiatives within the AI Simulation & Governance portfolio, moving projects seamlessly from discovery through delivery
• Translate complex workflows into intuitive, scalable user experiences that simplify data-intensive interfaces for enterprise users
• Present design rationale and concepts clearly to stakeholders and leadership, ensuring alignment between design vision and business goals
• Conduct user research and usability testing to validate design hypotheses and ensure customer insights meaningfully inform every product decision
• Leverage data and user insights to iterate on existing features, driving a continuous improvement cycle for the Conversational Cloud
• Contribute to and evolve our design system to ensure consistency and scalability across the entire product ecosystem
• Partner with Product and Engineering on roadmap planning and prioritization, ensuring technical feasibility without compromising on the user experience
• Champion accessibility and usability, ensuring all designs meet high standards of inclusivity (WCAG) and industry best practices

Product Designer – 6 Month Fixed Term Contract

Data Scientist

• Propose, plan, and execute applied research initiatives that will make a real-world impact on Conversational AI using Large Language Models (LLMs) within a commercial setting.
• Use expert knowledge of Transformer architecture mechanics (Attention, Tokenization, Embeddings) to consistently find the most effective, efficient, stable, explainable, and elegant prompting and orchestration approaches.
• Utilize modern LLM inference and retrieval pipelines.
• Analyze large scale conversational datasets for RAG (Retrieval-Augmented Generation) optimization.
• Bring research-inspired prompt strategies to life within production systems.
• Create durable, flexible scientific evaluation and experimentation capabilities for non-deterministic model outputs.
• Present findings on model behavior and context efficacy in ways that inform and guide business and product strategy.
• Work closely with other scientists.
• Stay current with the rapidly evolving state of Generative AI.

Data Scientist II

• Design and develop modernized Contact Center as a service Messaging and AI products that push the boundaries of what's possible
• Lead and mentor engineering teams, setting technical direction and best practices
• Partner with architecture team to shape requirements and translate vision into scalable solutions
• Part of SCRUM team(s) for day to day responsibilities.
• Design, implement cloud-native applications that are resilient, scalable, and built for the future
• Integrate and various solutions including Voice applications, platform SDK, LLM based AI solutions and services as required in the Product
• Drive engineering excellence through comprehensive test automation and quality-first delivery

Principal Engineer

• Provide Strategic Consulting: Be a subject matter expert and thought leader to help transform current and prospective customers. Deliver workshops, develop roadmaps, and present readbacks that address key business outcomes.
• Support Partner Sales: Collaborate closely with partners to drive sales efforts, ensuring alignment with LivePerson’s solutions, and take ownership of the partner relationship.
• Architect and Deliver Demonstrations: Build and deliver sophisticated demos around LivePerson's core platforms, including Conversational Cloud, Conversational AI, Voice AI, and Conversational Analytics, along with key partner technologies.
• Develop Sales Strategies: Partner with sales teams to strategize on winning opportunities, architecting new and custom solutions to showcase product integration into customer infrastructures.
• Provide Technical Expertise: Offer technical and industry expertise across various business units within LivePerson, including R&D, Marketing, and Partner Relations.
• Competitive Intelligence: Understand and relay information about competitors, adhering to ethical guidelines.
• Proposal Development: Collaborate on responses to RFPs, RFIs, RFTs, etc., and occasionally mentor new team members in Solution Consulting.
• Educational Support: Train Sales and Delivery teams on solutions and support customer conferences as a demo runner or speaker.

Senior Solutions Consultant

Sales

• Scale the North American enterprise team by identifying high-caliber Account Executives capable of navigating complex sales cycles
• Elevate team performance through coaching and personalized growth tracks, focused on moving high-potentials into top-tier performers and maintaining a culture of 'A-player' excellence
• Cultivate a transparent, high-energy environment that balances a competitive 'hunter' instinct with a collaborative 'win-as-a-team' philosophy.
• Define and manage the key performance indicators that drive success, proactively addressing underperformance while celebrating and rewarding over-achievement.
• Serve as the executive 'closer' on marquee deals, leveraging your presence to build trust with C-suite stakeholders at Fortune 500 prospects.
• Coach your team to pivot from 'feature selling' to 'value selling,' helping them articulate the business impact of Conversational AI.
• Architect high-opportunity clusters across North America, ensuring AE portfolios are balanced for optimal 'Land and Expand' potential.
• Participate in strategic deal reviews to help AEs navigate the complex stakeholder maps and procurement hurdles typical of multi-million dollar enterprise contracts.
• Maintain a pulse on the health of the North American sales funnel, providing executive leadership with accurate monthly and quarterly ARR projections.
• Refine the end-to-end sales lifecycle—from prospecting to closing—and ensure the team is effectively utilizing the sales tech stack (CRM, lead gen, etc.) to drive efficiency.
• Conduct rigorous pipeline reviews to ensure consistency in lead flow and to identify early-stage gaps.
• Act as the 'voice of the customer,' funneling insights from your AEs’ field experience back to Product teams to ensure the AI roadmap stays ahead of market demand.
• Partner with Marketing to optimize lead quality and ensure account-based marketing (ABM) efforts are tightly aligned with your team’s top-target accounts.

Director, Sales

• Develop and maintain automation solutions using Python, Terraform, and Bash to streamline deployment, configuration, and management of infrastructure and applications.
• Collaborate closely with development, operations, and other cross-functional teams to understand project requirements, create automation strategies, and deploy efficient solutions.
• Utilize cloud technologies and services, with a preference for Google Cloud Platform (GCP), to architect and manage scalable, secure, and highly available infrastructure.
• Troubleshoot issues across development, testing, and production environments, ensuring rapid resolution and minimal downtime.

Cloud DevOps III

• Maintain and support existing products within the Echo ecosystem.
• Ensure high availability, performance, and reliability of platform services.
• Define, monitor, and improve SLOs, SLIs, and error budgets.
• Proactively identify system risks and implement reliability improvements.
• Participate in incident response, troubleshooting, and post-incident reviews.
• Deploy, manage, and optimize workloads on Google Kubernetes Engine (GKE).
• Manage cluster capacity, scaling strategies, and resource allocation.
• Optimize CPU, memory, and storage utilization to improve performance and reduce cost.
• Ensure cluster security, upgrades, and best practices are followed.
• Troubleshoot networking, service mesh (if applicable), ingress, and service-to-service communication issues.
• Implement and manage GitOps-based deployment workflows.
• Ensure infrastructure and application changes are version-controlled and automated.
• Work closely with developers to safely release code to production using CI/CD best practices.
• Support progressive delivery techniques (e.g., canary, blue/green deployments).
• Reduce deployment risk through automation and validation mechanisms.
• Implement and enhance observability practices across services.
• Build and maintain dashboards, alerts, and health metrics.
• Implement and manage OpenTelemetry (OTEL) for tracing and metrics collection.
• Ensure proactive alerting aligned with SLOs.
• Drive improvements in monitoring coverage and signal quality.
• Strong understanding of Kubernetes networking, services, ingress, load balancing, DNS, and service communication.
• Diagnose latency, connectivity, and traffic routing issues.
• Understand how distributed services interact across the ecosystem.

Site Reliability Engineer II

Engineer

• Manage and enhance application security tools (Static Code Analysis, Open Source vulnerabilities tools, Dynamic Application Security tools, etc), integrations, and develop in-house application security automation tools
• Validate discovered vulnerabilities using code review skills and manual/semi-automatic tooling like Burp.
• Validate external penetration test results and work with internal and external stakeholders.
• Perform some security penetration tests (both application and infrastructure for Web and mobile applications)
• Work with the engineering and security teams to provide actionable reporting, find and explain security issues, suggest mitigations, and determine when issues are mitigated.
• Stay up to date on the latest testing tools and techniques ensuring both your and the team is using the most effective and efficient methods.
• Produce both high level and detailed reports and metrics to support data-based decisions.
• Assist in creating and updating Application Security procedures, policy, standards and guidelines
• Train, coach and mentor other members of the team, development and the broader LivePerson Security and Engineering teams.