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Get Well Network

Digital patient engagement platform for hospitals

Staff AI Engineer

Applied Machine Learning +1Confirmed live in the last 24 hours
Full-timeBengaluru, Karnataka, IndiaNo salary listedIn-person

About the Job

Requirements

  • A Master's degree or higher in Computer Science, Artificial Intelligence, Machine Learning, or a closely related technical field.
  • At least 10 years of experience, including a minimum of 3 years of technical experience in AI/ML technologies.
  • A proven track record of delivering complex AI solutions in healthcare or technologically advanced domains.
  • Deep technical proficiency in Large Language Model architectures, multimodal AI system design, and agentic system development using frameworks such as CrewAI, LangChain, and LangGraph.
  • Experience with machine learning model training and fine-tuning.
  • Experience with cloud computing infrastructure; AWS is preferred.
  • Experience with AI/ML frameworks and development tools such as TensorFlow, PyTorch, and Hugging Face.
  • Experience with AI monitoring and observability tools such as Langfuse, Prometheus, Grafana, or equivalent platforms.
  • Strong programming skills in Python, C++, or other relevant languages.
  • Experience with agile and adaptive project management methodologies.
  • Problem-solving and analytical skills focused on delivering scalable solutions.
  • Communication skills to explain complex technical concepts to non-technical stakeholders.
  • Experience working in cross-functional teams.
  • Ability to mentor junior engineers and contribute to team development.
  • Commitment to following organizational information security policies and protecting sensitive information, including ePHI and PHI, in accordance with federal, state, and local regulations.

Responsibilities

  • Design, develop, and implement AI solutions using unimodal and multimodal Large Language Models and agentic systems.
  • Develop and integrate agentic systems with frameworks such as CrewAI, LangChain, and LangGraph to enable autonomous decision-making and workflow automation.
  • Incorporate emerging AI technologies into product ecosystems to improve functionality and user experience.
  • Train and fine-tune models, and optimize inference engines for high-performance AI systems.
  • Ensure technical excellence in AI solution design and implementation.
  • Evaluate and integrate emerging AI technologies into existing systems.
  • Serve as the primary technical liaison between AI engineering and product teams.
  • Translate technical capabilities into product requirements and user-centric solutions.
  • Facilitate communication and alignment across engineering, product, and clinical teams.
  • Drive collaborative innovation and knowledge sharing.
  • Optimize cloud-based AI infrastructure for scalability, performance, and reliability.
  • Implement best practices for efficient AI system deployment and maintenance, including agentic workflows.
  • Establish and maintain testing and validation protocols for AI models.
  • Drive continuous improvement in AI model accuracy, efficiency, and robustness.
  • Implement and manage monitoring solutions for AI systems using tools such as Langfuse, Prometheus, Grafana, or equivalent platforms.
  • Analyze observability data to identify and resolve issues in AI model behavior, agentic system performance, and system reliability.
  • Develop proactive monitoring strategies to detect anomalies and ensure reliability of AI deployments.
  • Ensure AI solutions comply with healthcare regulatory standards and data privacy requirements, including HIPAA and GDPR.
  • Develop and enforce ethical AI guidelines to mitigate biases.
  • Ensure sensitive information, including ePHI and PHI, is handled securely in accordance with applicable regulations.

Desired Qualifications

  • AWS cloud computing experience is preferred.
  • Knowledge of healthcare technology landscapes and regulatory environments, such as HIPAA and GDPR.
  • Awareness of emerging AI technologies, including agentic systems, MCP, and A2A protocol, and their potential applications.

About the Company

Get Well Network

Digital patient engagement platform for hospitals

Get Well provides a cross-continuum digital patient engagement platform used by hospitals and health systems to engage patients before, during, and after a stay. It delivers personalized care journeys, educational content, and access to hospital services through bedside TVs, mobile apps, and computers, and includes automated Patient Pathways, virtual care, AI messaging, real-time feedback, and patient-reported outcomes, while integrating with 3,500+ health IT systems including EHRs. The platform differentiates through a B2B2C model and a focus on end-to-end care navigation and patient activation across the care continuum. Since its 2024 acquisition by SAIGroup, the company aims to accelerate AI-driven innovation, expand globally, and improve patient satisfaction and health outcomes.

Company size
201-500
Company stage
Series C
Total funding
$19M
Headquarters
Bethesda, MD
Founded
2000

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