Company Intro:
Encore Med is a health-tech company founded in 2016 focusing on innovating digital experience for healthcare operations and has a strong portfolio in transforming numerous business operations and processes for hospitals within the region.
Encore Med's vision is to help hospitals and healthcare institutes by providing patients with a simpler and smarter healthcare experience. Progressing with a team of 30 team members, Encore Med has been building sophisticated engines to meet complex hospital processes, innovating more products to ensure that the company products and services are moving ahead along with the technological advancements primarily in automation, artificial intelligence, and Internet-of-Things.
Job Summary:
The AI Product Manager is responsible for defining and delivering innovative AI-powered products and solutions. The role bridges business, technology, and data science, ensuring alignment between client needs, business objectives, and AI/ML feasibility. You will collaborate with stakeholders, data team, AI engineers, designers, and domain experts to conceptualize, validate, build, and iterate AI-driven features and experiences for existing and new products for the hospitals.
Job Requirements:
Product Strategy & Vision
- Define product vision, roadmap, and objectives for AI/ML-based initiatives.
- Identify market opportunities, emerging trends, and problems that AI can solve effectively.
- Translate business strategy into measurable product goals and OKRs.
User Research & Requirements
- Conduct deep user discovery (interviews, data analysis, survey, workflow mapping).
- Identify customer pain points and convert them into well-defined requirements.
- Write clear user stories, acceptance criteria, and product specifications.
- Work with R&D Engineer to quickly come up with prototype to test and validate with clients and market needs.
AI/ML Integration
- Partner with data science and engineering teams to identify viable models and approaches for healthcare (prediction, analysis, NLP, generative AI, etc.).
- Evaluate feasibility, model requirements, data availability, and training complexity with AI Engineers.
- Ensure AI practices: fairness, bias & hallucination mitigation.
Data Strategy
- Work with clients & data team to define required datasets, data collection pipelines, data analytics strategies.
- Ensure data quality, governance, compliance (GDPR, HIPAA, PDPA, etc.).
- Collaborate with data engineers to support analytics and model training.
Development Lifecycle
- Manage end-to-end product lifecycle; from concept prototype MVP production.
- Work closely with engineering to prioritize backlog, refine features, and deliver releases.
- Use iterative experimentation (AB testing, POC, pilots, shadow pilots).
Execution & Delivery
- Own product documentation, roadmaps, and release planning.
- Monitor KPIs post-launch: accuracy, adoption, user satisfaction, cost-efficiency, ROI.
- Work with sales & CS teams to support onboarding, implementation, and enablement.
Cross-functional Leadership
- Align with sales, marketing, UX/UI, operations, compliance, and leadership.
- Translate technical AI concepts into business-friendly narratives for stakeholders.
- Educate internal teams about AI product capabilities and limitations.
- Explore AI automation workflow for internal & external processes to reduce manual work.
Job Qualifications
- Bachelor's or master's degree in computer science, AI/ML, Data Analytics, Engineering, Business, or related field.
- 37 years experience in Product Management or equivalent.
- Experience with AI, ML products, analytics platforms, or data-driven systems.
- Knowledge of AI development lifecycle and cloud platforms(AWS/Azure/GCP).
- Exposure to software development and agile delivery.
- Passion for healthcare technology and a keen interest in optimizing operational excellence.
- Possesses an analytical mindset to extract and interpret data to drive informed decision-making.
- Exceptional communication and interpersonal skills to foster effective collaboration across diverse teams.
- Familiarity with agile methodologies and a solid grasp of the product development lifecycle.
- Basic understanding of user experience design principles to contribute to seamless interface design.
- Demonstrate ability to manage multiple tasks in a dynamic and fast-paced environment.
- String problem-solving skills coupled with a proactive approach to overcoming challenges.
- Experience within the healthcare, digital or SaaS industry is advantageous is a plus.
- Common AI techniques: NLP, recommendation systems, computer vision, anomaly detection.
- Data pipelines: ETL, feature engineering, training/validation cycles.
- Model evaluation metrics: accuracy, F1 score, ROC-AUC, precision/recall, MAPE.
- AI constraints: data volume, inference latency, domain biases, model drift.
