Job Title: Senior AI Engineer (LLM / Agent Systems)

Role Overview

Join a high-growth, venture-backed healthcare AI company building next-generation technology to transform clinical and operational workflows across post-acute care. The platform combines proprietary sensing technology, predictive analytics, and emerging AI capabilities to proactively identify risk and improve patient outcomes at scale.

The company is now expanding into a new AI-driven product layer focused on LLM-powered workflows and agent-based systems that unify clinical, operational, and financial data into a single intelligent interface. Think of it as a domain-specific AI platform enabling real-time decision-making across healthcare environments.

This role sits at the intersection of engineering, product, and customer delivery. You will design and deploy production-grade AI agents, work directly with customers, and play a key role in shaping how AI is applied in real-world clinical settings.

Key Responsibilities:

• Design and deploy LLM-powered agents and workflows for real-world use cases (e.g., automation, insights, operational decisioning)
• Translate ambiguous customer requirements into scalable, production-ready AI systems
• Build and integrate pipelines across APIs, data platforms, and external systems (REST, webhooks, event streams)
• Configure and optimize RAG pipelines, vector databases, and context management systems
• Partner with Sales during pre-sales to prototype solutions, whiteboard architectures, and define implementation scope
• Own end-to-end delivery from initial prototype through production deployment and iteration
• Analyze system performance (accuracy, hallucination rates, outcomes) and continuously improve models and workflows
• Collaborate cross-functionally with engineering, product, and customer stakeholders
• Travel to customer sites (~25%) to support deployments, training, and executive presentations
• Identify expansion opportunities and support additional use cases post-deployment

Education & Qualifications:

• 5–10+ years of experience in software engineering, AI engineering, solutions engineering, or similar hands-on technical roles
• Strong experience building and shipping production systems (not just prototypes or research work)
• Proficiency with APIs, integrations, and backend development (Python, Node.js/TypeScript, or similar)
• Experience working with LLMs and modern AI tooling (OpenAI, Anthropic, or similar ecosystems)
• Familiarity with agent frameworks, RAG architectures, or context orchestration systems
• Ability to operate in ambiguous environments and take full ownership of outcomes
• Strong communication skills with the ability to translate complex technical concepts to non-technical stakeholders
• Comfortable working in a fast-paced, high-growth startup environment

Preferred Experience:

• Hands-on experience with tools such as LangChain, LangGraph, AutoGen, DSPy, or similar frameworks
• Experience building AI systems that interact with real-world data (e.g., time-series, operational systems, or large-scale datasets)
• Background in regulated environments (e.g., healthcare, fintech, or similar)
• Experience owning both pre-sales and post-sales technical delivery
• Exposure to enterprise system integrations (e.g., event-driven architectures, streaming, or workflow automation)
• Advanced degrees (MS/PhD) from strong technical programs are valued but not required

Why Us:

• Opportunity to build next-generation AI systems with real-world impact at scale
• Work on a new product initiative centered around LLMs, agents, and intelligent workflows
• High ownership role with direct influence on product direction and customer outcomes
• Fast-growing company with strong traction and significant enterprise demand
• Work alongside a highly technical, mission-driven team focused on meaningful problems
• Exposure to both cutting-edge AI and real-world deployment challenges

Benefits and Perks:

• $120k-220k DOE + bonus + equity
• 100% company-paid medical, dental, and vision insurance
• 401(k) with company match
• Generous PTO
• Paid parental leave
• Commuter benefits
• Professional development support
• Company retreats and team events

Applicants must be currently authorized to work in the United States on a full-time basis now and in the future. This position does not offer sponsorship.

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Job Title: Account Executive – Enterprise Sales

Role Overview

Join a fast-growing, venture-backed healthcare AI company transforming how care is delivered across senior living and post-acute environments. This organization has built a proprietary platform that combines advanced sensing technology, predictive analytics, and deep integrations into clinical and operational workflows to proactively prevent adverse health events.

With strong market traction, significant enterprise contracts already in place, and rapid expansion underway, this is a high-impact opportunity to join as an early sales hire. You’ll work directly with leadership, help shape the go-to-market motion, and play a critical role in scaling revenue within a largely untapped market.

This is a highly hands-on, field-driven role. Success comes from being in front of customers, building trust on-site, and delivering compelling product experiences that drive adoption across multi-location operators.

Key Responsibilities:

• Own a geographic territory and manage the full sales cycle from initial engagement through close
• Convert warm, qualified pipeline into revenue, focusing on enterprise-level deals (~$600K+ ARR)
• Deliver high-impact, in-person product demonstrations at customer facilities; demos are central to closing deals
• Travel 50%+ to meet prospects, tour facilities, and build relationships with decision-makers
• Sell into both corporate leadership and on-site operators across multi-location organizations
• Land initial deals across multiple facilities and expand across broader enterprise networks
• Partner closely with executive leadership to refine messaging, sales strategy, and demo approach
• Maintain strong CRM discipline including pipeline tracking, forecasting, and follow-up execution
• Represent the company at industry events, conferences, and trade shows

Education & Qualifications:

• 3–10+ years of experience selling technology, software, or services into physical-location businesses (e.g., retail, restaurants, facilities, or similar environments)
• Proven success managing full-cycle enterprise or mid-market sales processes
• Strong field sales orientation with a preference for in-person, relationship-driven selling
• Experience selling into multi-location operators or enterprise accounts
• Exceptional product demo skills with the ability to tailor messaging to different audiences
• Consultative sales approach focused on customer problems and business outcomes
• Comfortable operating in a fast-paced, high-growth environment with evolving processes
• Based in Los Angeles or willing to align with assigned territory and travel regularly

Preferred Experience:

• Background selling into industries such as retail tech, POS systems, IoT, operational platforms, or facility management solutions
• Experience in healthcare, senior care, or other regulated industries
• Early-stage or founding AE experience within a startup environment
• Exposure to both hardware and software sales motions
• Experience working with enterprise buyers across multiple stakeholder groups

Why Us:

• Join as one of the first sales hires and directly influence go-to-market strategy
• Strong existing traction with enterprise customers and a large pipeline of opportunities
• Founder-led sales transitioning to a scalable revenue organization
• Opportunity to sell a differentiated product with clear ROI and real-world impact
• High visibility role with direct access to executive leadership
• Massive market opportunity with long-term expansion potential across enterprise accounts

Benefits and Perks:

• $120k-180k DOE + uncapped commission tied to closed revenue
• Equity in a high-growth, venture-backed company
• 100% company-paid medical, dental, and vision insurance
• 401(k) with company match
• Paid parental leave
• Generous PTO
• Commuter benefits
• Modern office environment with team events and perks

Applicants must be currently authorized to work in the United States on a full-time basis now and in the future. This position does not offer sponsorship.

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Job Title: Principal Machine Learning Engineer
Role Overview

A rapidly growing healthcare AI company is transforming how clinicians monitor and care for vulnerable populations. The organization builds predictive health technology that combines contactless sensing devices with advanced machine learning to detect early signs of patient deterioration. Their platform analyzes physiological signals and clinical data to help healthcare providers intervene earlier and prevent avoidable hospitalizations.

With thousands of patients monitored daily across post-acute care environments, the company is expanding its engineering team to further advance the predictive models at the core of its platform. This role sits at the intersection of applied machine learning, healthcare data, and real-world deployment.

The Principal Machine Learning Engineer will own the end-to-end lifecycle of predictive models that power clinical decision support and operational workflows used in production environments. This individual will contribute to both improving existing risk prediction models and exploring new applications of machine learning across clinical and biometric datasets.

This is a hands-on, high-impact role for someone who enjoys solving complex ML problems with real-world consequences, building models that must perform reliably on messy real-world data, and rapidly iterating in a startup environment where shipped models directly affect patient outcomes.

Key Responsibilities

• Design, train, and continuously improve production-grade machine learning models for predictive risk scoring, clinical classification, and health deterioration detection
• Apply statistical learning approaches including gradient boosting methods (such as XGBoost, LightGBM, CatBoost) as well as modern deep learning approaches including transformer-based architectures where appropriate
• Work with time-series and longitudinal datasets derived from physiological signals, vital signs, and operational healthcare data
• Design experiments to evaluate new modeling techniques, feature engineering strategies, and training approaches that improve predictive performance
• Own the full model lifecycle from research and experimentation through validation, production deployment, monitoring, and iteration
• Develop and maintain feature pipelines that transform raw sensor data, clinical indicators, and behavioral signals into model-ready datasets
• Collaborate closely with clinicians, engineers, and product stakeholders to ensure models are interpretable, clinically useful, and aligned with real-world workflows
• Contribute to exploration of new AI capabilities, including applications of large language models (LLMs) for clinical documentation and workflow optimization
• Investigate new signal sources and data modalities that may improve prediction accuracy or enable new product capabilities
• Produce explainability outputs (such as SHAP or feature attribution) to support transparency, auditing, and trust in model predictions
• Partner with engineering teams to deploy models into production systems through APIs and scalable pipelines
• Measure real-world impact of models using operational and clinical outcome metrics
• Contribute technical leadership in shaping modeling direction and future ML team expansion

Education & Qualifications

• 5–10+ years of experience developing and deploying machine learning models in production environments
• Strong hands-on experience applying statistical and machine learning techniques to real-world datasets
• Experience improving model performance through experimentation, feature engineering, or training optimization
• Advanced Python expertise and experience with ML tooling such as NumPy, pandas, scikit-learn, PyTorch, TensorFlow, or similar frameworks
• Strong foundation in statistics, machine learning theory, and model evaluation methodologies
• Experience working with structured, tabular, or time-series datasets
• Demonstrated ability to own ML projects end-to-end, from experimentation through deployment and monitoring
• Ability to communicate technical trade-offs and model behavior to cross-functional stakeholders
• Comfort working in ambiguous problem spaces where experimentation and iteration are required
• Experience collaborating with distributed teams across time zones is a plus

Preferred Experience

• Experience working in healthcare, life sciences, insurance, fintech, or other regulated industries
• Exposure to clinical prediction problems, early warning systems, survival modeling, or anomaly detection
• Experience working with sensor data, physiological signals, or real-world behavioral datasets
• Familiarity with LLM-enabled systems or modern AI-assisted workflows
• Experience evaluating or developing models using deep learning or transformer-based architectures
• Startup experience where ML models directly influenced product outcomes or user workflows
• Publications, patents, or technical writing related to applied machine learning
• Experience mentoring other ML engineers or contributing to technical direction

Why Join

• Opportunity to build machine learning systems that directly influence real-world healthcare outcomes
• Work in a fast-moving environment where models are deployed quickly and continuously improved
• Direct collaboration with clinicians, engineers, and product leaders solving meaningful healthcare problems
• High ownership role helping shape the future direction of a predictive health platform
• Exposure to diverse machine learning challenges spanning statistical modeling, deep learning, and emerging AI technologies
• Strong growth trajectory with increasing demand for predictive healthcare technologies

Benefits and Perks

• Competitive base salary range: $160,000 – $260,000 plus meaningful equity participation
• 100% company-paid medical, dental, and vision coverage
• 401(k) with employer match
• Generous paid time off
• Collaborative headquarters workspace with team events and weekly team lunches
• Opportunity to work on technology that directly impacts patient care and healthcare outcomes

Applicants must be currently authorized to work in the United States on a full-time basis now and in the future. This position does not offer sponsorship.

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