About the Organisation
The Antara Foundation (TAF) envisions a world where women and children do not suffer from preventable health conditions. We believe that every mother and every child deserves an equal start to a healthy life. We support the public health system in delivering solutions on a scale to improve maternal and child health outcomes by partnering with the government and communities. Interventions of The Antara Foundation follow two closely integrated paths: to help the government system deliver higher-quality health care to the community and to support the community in mobilising and seeking better health outcomes.
About the Position
TAF’s Digital Public Health Program is building the next generation of scalable, interoperable digital health systems in India, combining WhatsApp-based nudging, workflow automation, conversational AI, and data-driven decision support. After developing initial sets of solutions and a healthy partner ecosystem, we are now looking to expand our in-house technical development capabilities.
The Data & AI Engineer will power the data and intelligence backbone of TAF’s digital health stack. You will design and operationalise pipelines that bring together structured health data, conversational AI, and predictive analytics, translating complex systems into usable, ethical, and field-ready digital tools. If you are passionate about applying data and AI for the public good, this role offers an opportunity to shape India’s next generation of digital health systems.
Duty Station: Delhi (with travel to program locations)
Reporting to: Chief Strategy Officer – Digital Health
Key Responsibilities
- Design and implement scalable data architectures integrating Sheets, Excel, and government systems into cloud databases (PostgreSQL, BigQuery).
- Develop APIs and ETL workflows for data ingestion, transformation, and retrieval across GCP-based systems.
- Design and orchestrate Gemini/LLM pipelines for conversational reasoning, data interpretation, and predictive insights.
- Build ASR–LLM–TTS pipelines optimised for multilingual, low-resource contexts (Hindi + regional languages).
- Manage embeddings and vector databases for contextual retrieval and knowledge grounding.
- Translate backend intelligence into usable insights for health workers, dashboards, chatbots, and community feedback loops.
- Collaborate with program teams to ensure AI models reflect real public health needs, ethics, local contexts, and are validated against field realities, including low-connectivity environments.
- Support rapid data visualization for program dashboards and government review systems
- Establish data security, versioning, and model monitoring best practices.
Skills and Experience
- Education: B.Tech/M.Tech in Computer Science, Data Science, or related discipline.
- Experience: 3–6 years of experience in backend, data engineering, or AI-driven product development; exposure to health, GovTech, or social impact data preferred.
Technical Skills
- Languages: Python (Pandas, FastAPI, LangChain, SQLAlchemy).
- Databases: PostgreSQL, BigQuery, SQLite; vector DBs such as Pinecone, FAISS, or Chroma.
- AI/LLM: Gemini API, LangChain, prompt design and orchestration.
- Speech Tech: Experience with ASR (Whisper, Google Speech) and TTS (Coqui, ElevenLabs). Experience applying NLP to unstructured text/audio for community feedback and AI-enabled sensemaking.
- Cloud: Google Cloud Platform (Cloud Run, Cloud Functions, BigQuery, Secret Manager); experience with containerized workflows using Docker.
- Data Pipelines: End-to-end ETL development, schema design, data validation, logging, and performance monitoring.
- Visualization: Experience with tools such as Streamlit, Gradio, Looker Studio, Power BI, and user journey mapping for rapid analytics and insight generation.
Personal Attributes
- A curious, iterative builder with strong attention to data quality and integrity.
- Belief in AI for inclusion and public good.
- Comfortable explaining complex systems to non-technical stakeholders.
- Collaborative, detail-oriented, and driven by problem-solving.
