Job description

In this role, you have the opportunity to

Turn advanced analytics, machine-learning models and GenAI capabilities into simple, scalable and usable People Analytics products.

You will be responsible for developing lightweight internal applications, APIs, deployment workflows and monitoring solutions that allow the People Analytics team to take products from development into production.

Your work will help ensure that People Analytics solutions are not limited to notebooks or proofs of concept, but can be securely deployed, adopted, supported and improved over time.

You are responsible for

Developing lightweight, scalable internal applications for People Analytics use cases.
Building conversational interfaces, analytical applications and decision-support tools.
Developing APIs that connect user interfaces with data, machine-learning models and GenAI services.
Integrating applications with enterprise authentication and role-based access controls.
Implementing application logging, error handling and user-feedback mechanisms.
Packaging analytical and AI solutions for deployment into IT-managed environments.
Building and maintaining product-specific CI/CD pipelines in line with enterprise standards.
Automating code testing, application testing and deployment activities.
Managing application configurations across development, test and production environments.
Working with IT to provision and configure required cloud and platform services.
Supporting deployment, release management, rollback and recovery activities.
Operationalising batch and real-time model inference.
Supporting model-serving and GenAI-service integration.
Implementing monitoring for application availability, performance, latency, usage and errors.
Supporting the monitoring of model and GenAI components in collaboration with the Applied AI and ML Engineer.
Creating reusable application templates and common technical components.
Standardising authentication, API, logging, monitoring and feedback patterns across People Analytics products.
Providing business-hours technical support for deployed applications.
Diagnosing application, integration and deployment issues.
Coordinating infrastructure-related incidents with IT teams.
Maintaining technical documentation, support runbooks and release records.
Contributing to ongoing enhancements and product improvements after launch.

You are a part of

The central People Analytics team within the People Intelligence organisation.

The team builds predictive, prescriptive and AI-enabled products for People Business Partners, business leaders and People-function Centres of Expertise across Philips.

You will work closely with:

The People Analytics Lead
Data Scientists
People Data Engineers
Applied AI and Machine Learning Engineers
People Intelligence Analytics Partners
Enterprise IT, cloud, platform and security teams

To succeed in this role, you will need

A bachelor's or master's degree in computer science, software engineering, information technology, engineering or a related field.
Relevant professional experience in software engineering, analytics application development, DevOps, MLOps or a related domain.
Strong Python software-engineering skills.
Experience developing REST APIs using FastAPI, Flask or equivalent frameworks.
Experience developing internal applications using Streamlit, Dash or similar frameworks.
Experience with automated testing and code-quality practices.
Experience with Git and modern version-control workflows.
Experience configuring and using CI/CD pipelines.
Understanding of containerisation and cloud-deployment concepts.
Experience integrating applications with authentication and role-based access controls.
Experience implementing logging, monitoring and alerting.
Familiarity with Databricks and cloud-based data or AI services.
Experience troubleshooting applications in production or controlled enterprise environments.
The ability to translate analytical requirements into maintainable technical products.
Strong collaboration and communication skills.
A pragmatic approach to technology, with the ability to balance scalability with speed and simplicity.

Preferred experience

Experience with Azure, AWS or both.
Experience with Azure App Service, AWS application services or equivalent platforms.
Experience with Docker and Kubernetes fundamentals.
Experience integrating with enterprise API gateways.
Experience with MLflow, model-serving platforms or MLOps tools.
Experience integrating GenAI or RAG capabilities into applications.
Experience with React or another front-end framework.
Experience with enterprise identity and access-management systems.
Understanding of application-security practices.
Experience building internal data, analytics or AI products.
Experience working with sensitive or employee-level data.
Experience operating in global, matrixed organisations.

Key capabilities

Application engineering

API development

MLOps

DevOps and CI/CD

Cloud application deployment

Monitoring and observability

Python engineering

Authentication and access control

Production support

GenAI application integration

Technical ownership

How we work together

We believe that collaboration and effective ways of working are essential to building meaningful solutions. For this role, we prefer candidates who can work from Bangalore and collaborate closely with local and global stakeholders.

About Philips

We are a health technology company. We built our entire company around the belief that every human matters, and we will not stop until everybody everywhere has access to the quality healthcare that we all deserve.

Doing meaningful work with people who share our passion for improving lives is what makes Philips a unique place to work.