Infinitus Systems, Inc.

Customer Success Manager

• Own enterprise accounts end-to-end: from onboarding through renewal and expansion, serving as the primary strategic contact across the full customer lifecycle
• Drive ongoing customer health and success: conduct regular check-ins, usage and outcomes monitoring, Quarterly Business Reviews (QBRs), and proactive outreach to ensure value realization and early issue detection
• Identify and convert growth/expansion opportunities: map customer needs, identify new/expansion use cases, and partner with Sales to grow adoption across customers’ business units and departments
• Support implementation and adoption: partner with our Enablement team on integrations, workflow design, technical launches, and user training to ensure rapid time-to-value and stable onboarding
• Collaborate cross-functionally: partner with Product, Engineering, Sales, Marketing, Operations, and Finance/RevOps to resolve roadblocks, support billing and invoicing accuracy, and coordinate expansions or new pilots for existing accounts
• Maintain strong account operations and hygiene: maintain CRM/CS tool records, manage communications, issue resolution, renewal tracking, and billing/invoice checks as needed
• Advocate for the customer internally: collect feedback, surface product or workflow enhancement ideas, and help inform product roadmaps based on real-world usage and needs
• Build and deepen relationships across stakeholders: from end-users to senior executives, earn trust, influence adoption, and drive enterprise-level engagement

Analyst

• Document client requirements and create and maintain technical specifications. Analyze client legacy data sets to understand the impact of the data on system design as needed.
• Configure the Infinitus platform in response to requirements with a best-practices mentality. Leverage structured project delivery methodology.
• Establish CSV-based, API-based and other standard-based integrations with client systems like Patient Relationship Management and Electronic Medical Records etc.
• Support QA, client UAT, and launch processes.
• Provide support in client meetings by leveraging in-depth knowledge of our platform capabilities.
• Partner with client and internal teammates to resolve technical issues/inquiries.
• Act as our first line of support, owning resolution and client communication.
• Manage multiple client implementations concurrently

Implementation Analyst – Customer Enablement Specialist

AI Engineer

• Lead all product efforts around the foundation of our AI platform, covering a broad range of initiatives involving AI automation, AI safety, Knowledge Graph, analytics and insights, financial systems, and more.
• Lead the definition of AI solutions for our customers, identifying and launching new capabilities needed to deliver end-to-end offerings for customers.
• Interview prospective customers and users, analyze competitors, and identify opportunities for new use cases.
• Define the value proposition and offerings for new capabilities in our AI platform, as well as new end-to-end AI solutions, balancing short-term feasibility and long-term success.
• Define the target outcomes and key success metrics, partnering with engineering, operations, and go-to-market teams (sales, marketing, and customer success) to execute.
• Share insights across product, engineering, and other teams to build empathy for our target customer and users.
• Act as the external and internal spokesperson for our agentic communications platform.

Product Manager, AI Platform

Engineer

• Design, build, and maintain scalable Salesforce managed packages for Health and Life Sciences Cloud.
• Own the process of publishing managed packages on Salesforce AppExchange, including packaging, versioning, and namespace management.
• Work closely with Salesforce product and engineering teams to deliver innovative, native solutions.
• Gather customer requirements and deliver managed packages that ensure seamless integration and adoption.
• Collaborate across Infinitus teams (product, engineering, customer success) to deliver secure, scalable solutions for multiple Salesforce orgs.
• Participate in code reviews, testing, and deployment using CI/CD best practices.
• Ensure code quality, security, and performance, following Salesforce and industry standards.
• Troubleshoot, debug, and optimize Salesforce implementations and workflows.
• Build robust integrations between Salesforce and external systems (REST/SOAP, Infinitus APIs, healthcare APIs).
• Implement secure authentication (OAuth, token-based) and data flows.
• Develop, test, and deploy Apex callouts, platform events, and asynchronous processes.
• Write, review, and optimize Apex classes, triggers, batch jobs, and Visualforce pages.
• Build Lightning Web Components (LWC) and Aura components.
• Design and implement custom objects, fields, and data flows.
• Move data between standard objects and managed package namespaces.

SFDC Engineer – Mid Career

Backend Engineer

• Design, build, and maintain scalable backend services and APIs that power Eva’s healthcare interactions.
• Collaborate closely with Data Science, Frontend, and Infrastructure teams to bring AI and NLP solutions into production.
• Make technical tradeoffs to balance impact, user experience, and long-term scalability.
• Champion engineering best practices, including reducing technical debt and improving reliability.
• Mentor junior engineers and contribute to growing a high-performing engineering culture.
• Partner with product managers, designers, and analysts to deeply understand user needs and deliver impactful solutions.
• Contribute to both short- and long-term technical roadmaps.

Backend Engineer – Mid Career

Salesforce Developer

• Design, build and scale Managed Package Apps for new and existing customers in Salesforce Health and Life Sciences Clouds.
• Provide technical guidance and best practices for Salesforce and MuleSoft integrations to influence customer's Salesforce implementations
• Optimize customer workflows for high availability, scalability, and performance.
• Participate in pre-sales activities, including technical presentations, solution demonstrations, and proposal development for prospective clients.
• Collaborate with sales and customer success teams to understand prospect requirements and propose tailored solutions.
• Manage multiple client projects concurrently, ensuring timely delivery and client satisfaction.
• Understand system configuration issues, data integration issues and any other technical set up internally or with customer systems.
• Design and develop MuleSoft applications to integrate Salesforce Health and Life Sciences Clouds with Infinitus APIs, using FHIR standards.
• Design and expose REST APIs for system interoperability.
• Document client requirements and create technical specifications.
• Configure the Infinitus platform and establish integrations with client systems.
• Support QA, UAT, and launch processes.
• Partner with internal teams and clients to resolve technical issues.

Salesforce Solution Architect, Pharma

Product Specialist

• As a Clinical Product Specialist, you will give voice to patient and clinician perspectives in the products we build.
• You will partner with product managers and conversation designers to ensure our agents communicate with care and empathy.
• You will conduct product demos for customers, creating clinical scenarios that are relatable and compelling.
• Leveraging your experience in patient care, you will play a key role in delivering products that better connect patients and their care teams throughout their healthcare journey.
• Your clinical training and intuitive understanding of a patient’s journey will be instrumental as we introduce Infinitus AI agents in patient-facing conversations.
• Your role is essential for patient experience and ensuring successful deployment of AI in healthcare.

Clinical Product Specialist

Product Manager

• Lead all product efforts around the foundation of our AI platform, covering a broad range of initiatives involving AI automation, AI safety, payor intelligence, analytics and insights, financial systems, and more.
• Lead the definition of AI solutions for our customers, identifying and launching new capabilities needed to deliver end-to-end offerings for customers.
• Interview prospective customers and users, analyze competitors, and identify opportunities for new use cases.
• Define the value proposition and offerings for new capabilities in our AI platform, as well as new end-to-end AI solutions, balancing short-term feasibility and long-term success.
• Define the target outcomes and key success metrics, partnering with engineering, operations, and go-to-market teams (sales, marketing, and customer success) to execute.
• Share insights across product, engineering, and other teams to build empathy for our target customer and users.
• Act as the external and internal spokesperson for our AI platform foundation and solutions built upon the platform.

Product Manager – AI Foundation and Solutions

Account Executive

• Achieves sales objectives and quota by providing independent sales coverage of assigned accounts or within assigned territory, as well as client retention of assigned territory.
• Successfully position value / benefits with “C level” decision makers.
• Contribute to sales pipeline growth through Growth & Retention initiatives (3-4x quota).Match your deep knowledge of clients to a short- and long-term solution roadmap with expected value and results creating a trusted high-performance partner/advisor relationship.
• Source new sales opportunities through inbound lead follow-up and outbound cold calls and emails.

National Account Executive

Machine Learning Engineer

• Apply **strategic AI thinking** to solution development.
• **Mentor, guide, and influence** teams of engineers.
• Engage in **hands-on, impactful work** that directly benefits customers and the business.
• Blend **traditional machine learning, deep learning, and large language models (LLMs)** to maximize performance and scalability.

ML Engineer – Early Career, Mid Career

Human Resources

• Serve as the primary People Team partner to Operations leaders and their teams, building strong, trusted relationships at all levels.
• Own day-to-day people processes for our distributed Operations team.
• In partnership with leaders, this role will manage employee relations matters, including investigations, disciplinary actions, and performance conversations.
• Coach and support managers.
• Partner with cross-functional stakeholders.
• Analyze trends and metrics to identify opportunities for improvement.
• Support change management and communication strategies.
• Promote a culture of feedback, accountability, and inclusion across Operations teams.
• Ensure compliance with federal, state, and local employment laws and internal policies.

Human Resources Business Partner

• Document client requirements and create and maintain technical specifications. Analyze client legacy data sets to understand the impact of the data on system design as needed.
• Configure the Infinitus platform in response to requirements with a best-practices mentality. Leverage structured project delivery methodology.
• Establish CSV-based, API-based, and other standard-based integrations with client systems like Patient Relationship Management, Case Management, and Electronic Medical Records, etc.
• Support design, development, QA, UAT, and launch system integrations with our Infinitus Platform.
• Provide support in client meetings by leveraging in-depth knowledge of our platform capabilities.
• Partner with client and internal teammates to resolve technical issues/inquiries.
• Act as our first line of support, owning resolution and client communication.
• Manage multiple client implementations concurrently.

Healthcare Integrations Analyst

Full-stack Engineer

• Develop real-time, dynamic web front-ends for our conversational AI applications, employing the latest in ReactJS, TypeScript, Material UI, GraphQL, and WebSockets.
• Lead UX/UI design initiatives, from conceptual workflows to high-fidelity product designs, ensuring our solutions are aligned with user needs.
• Analyze user behavior to optimize UX flows (we’re very focused on user efficiency with our frontend)
• Collaborate on backend development, enhancing APIs and database schemas in partnership with backend engineers to build sophisticated business logic.
• Serve as a mentor to junior engineers, guiding their development and fostering a culture of technical excellence and collaborative growth.

Full Stack Engineer, Mid Career

• Build and maintain frontend/backend services that power our healthcare products.
• Help design and develop scalable APIs and integrations.
• Collaborate with data science and infrastructure engineers on end-to-end solutions.
• Write clean, testable, and maintainable code with guidance from senior engineers.
• Participate in code reviews, technical discussions, and roadmap planning.
• Gain experience in performance optimization, reliability improvements, and scaling systems.
• Work with AI coding tools (Cursor, Claude Code, etc.)
• Work with product managers and designers to understand user needs and deliver real customer value.
• Learn best practices in frontend/backend engineering and grow into increasing ownership over time.

Full Stack Engineer – Early Career

Data Scientist

• Define and Own Conversational AI Metrics: Develop, refine, and track key performance indicators (KPIs) for our voice agents, including automation rates, task completion success, conversation quality, adherence to guidelines, and human intervention metrics.
• Drive Automation Quality Improvements: Analyze conversation logs, model outputs, and user interactions to identify patterns, root causes of errors (e.g., dialogue breakdowns, misunderstandings), and key opportunities for improving automation quality and user experience. Where applicable, proactively implement improvements to voice agents
• Lead Experimentation and Analysis: Design, execute, and analyze experiments to evaluate the impact of changes to prompts, dialogue strategies, underlying ML models , and knowledge retrieval mechanisms.
• Inform Strategy through Data: Provide data-driven insights to guide decisions on model fine-tuning priorities, prompt optimization efforts, operator routing logic, and potential areas for new automation strategies.
• Analyze Specific Interaction Challenges: Investigate complex issues like dialogue breakdown signals, the effectiveness of knowledge retrieval during calls, and performance variations across different call types or languages (e.g., evaluating readiness for Spanish/Cantonese/Mandarin).
• Collaborate Cross-Functionally: Work closely with Product Managers, Machine Learning Engineers, Software Engineers, and Conversation Designers to translate insights into action, influence the product roadmap, and ensure data-driven decision-making across the team.
• Communicate Insights Effectively: Craft compelling narratives and visualizations based on data to communicate findings, progress, and recommendations to technical and non-technical stakeholders.

Data Scientist – Mid Career

Data Analyst

• Lead high-impact analysis: Design and deliver advanced statistical, predictive, and optimization models that shape executive-level strategy and operational decisions.
• Build better tools: Lead the development of AI-powered analytics and automated reporting systems to improve performance and outcomes.
• Drive insight at scale: Create and maintain KPIs, dashboards, and monitoring systems that identify trends, uncover opportunities, and guide business strategy.
• Collaborate deeply: Work closely with cross-functional teams to integrate analytics into product roadmaps, operational processes, and strategic initiatives.
• Mentor and elevate: Help junior analysts grow their skills in analysis, communication, and technical execution.
• Safeguard data integrity: Ensure analytics work meets rigorous compliance, governance, and privacy standards—especially in a regulated healthcare environment.

Data Engineer

• Create the systems, standards, and mentorship that empower partner teams and unlock new, scalable use cases for data.
• Help define our data architecture and pipeline design as we grow. Owning data engineering best practices and platform design.
• Collaborate with partner teams to enable faster consistent data delivery and reliable metrics.
• Help partner teams design better systems, access better insights, and ship better data solutions through tooling, guidance, and training.
• Expand and maintain deployment processes, testing, monitoring, and documentation that let us ship confidently.

Data Engineer – Early Career, Mid Career

Artificial Intelligence

• Assisting the Infinitus AI system in completing verification phone calls through our proprietary platform
• Ensuring quality of recorded outputs
• Working with operations and engineering teams to train the Infinitus AI platform to improve healthcare data collection
• Researching healthcare treatments, insurance providers, and reimbursement models
• Periodic mandatory overtime throughout the year is required in Operations.

AI Trainer

• Build and maintain backend services that power our healthcare products.
• Help design and develop scalable APIs and integrations.
• Collaborate with data science, frontend, and infrastructure engineers on end-to-end solutions.
• Write clean, testable, and maintainable code with guidance from senior engineers.
• Participate in code reviews, technical discussions, and roadmap planning.
• Gain experience in performance optimization, reliability improvements, and scaling systems.
• Work with AI coding tools (Cursor, Claude Code, etc.)
• Work with product managers and designers to understand user needs and deliver real customer value.
• Learn best practices in backend engineering and grow into increasing ownership over time.

Backend Engineer – Early Career

Analytics Engineer

• Shape our analytics foundation: Define modeling patterns, metrics architecture, and analytics engineering best practices as we grow. Owning transformation design from raw data to consumption ready marts.
• Enable stakeholders: Collaborate with Product, Operations, Engineering, and Analytics teams to deliver faster, more reliable insights that drive business decisions.
• Build capacity: Mentor analysts and data consumers through tooling, guidance, and training—helping them design better models, build better metrics, and ship better insights.
• Scale with quality: Expand and maintain testing and documentation that let us ship confidently and sustainably.