Full stack - AI Application Engineer - People Analytics
AI in this role
Full stack AI application engineer turning machine learning and GenAI capabilities into scalable people analytics products.
Job Title
Full stack - AI Application Engineer - People AnalyticsJob Description
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.
How we rate this
Full stack - AI Application Engineer - People Analytics at Philips rates 75 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
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Skills and AI tools this role asks for
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you monitor a model once it's live, and how do you know it needs retraining?
- Tell me about a project where full stack was part of your work. What did you do?
- Tell me about a project where machine learning was part of your work. What did you do?
- Tell me about a project where api integration was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: RAG, ML Ops, Full Stack, Machine Learning, and API Integration. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.
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