About TartanHQ
TartanHQ is an AI-first enterprise-tech company backed by 500 Global, Info Edge Ventures, and AngelList. We've raised $8.5M and are rapidly scaling toward profitability. Our platform powers operations for India's leading financial institutions including HDFC Bank, Bajaj Allianz, Care Health, Yes Bank, and 50+ enterprises.
We provide three core products: HyperVerify (80+ verification APIs), HyperSync (unified APIs for HRMS/ERP/CRM), and HyperApps (AI agents for insurance, banking, and compliance automation).
Role Overview
We are seeking an AI Engineer / Data Scientist with 2-6 years of experience to develop AI models, data pipelines, and intelligent features for TartanHQ's products. You will design and deploy production-ready AI systems, collaborate with product managers on AI requirements, and build the data infrastructure powering our AI layer. This role combines software engineering rigor with machine learning expertise to deliver measurable AI-driven value.
Key KPIs
- AI feature delivery: 1 new feature/POC per month
- Unit test coverage: 100%
- Sprint delivery: >90%
- Code quality: 100% PR reviews
- Model performance: Meets production SLAs
Day-to-Day Responsibilities
Your week includes: designing and training AI models, writing production code with tests, collaborating with product and engineering, sprint ceremonies and standups, debugging model performance issues, and knowledge sharing. You'll work on the full lifecycle from model development to production deployment.
Core Responsibilities
AI Development Excellence (55-60% time allocation)
- Design and develop robust AI models using TensorFlow, PyTorch, or Scikit-learn
- Build at least 1 new AI feature or POC every month
- Develop production-ready code with 100% unit test coverage
- Implement scalable data pipelines for model training and inference
- Deploy models using containerization and cloud platforms
- Optimize model performance and latency
- Investigate and resolve production issues with RCA
Team & Codebase Excellence (15% time allocation)
- Improve code quality and system scalability
- Actively reduce technical debt and system issues
- Participate in code reviews with high standards
- Contribute to engineering best practices
Knowledge Sharing & Learning (5-10% time allocation)
- Conduct knowledge-sharing sessions on AI/ML topics
- Mentor junior engineers and interns
- Guide team on coding standards and architecture
- Stay updated with latest AI/ML trends
Required Skills & Qualifications
- 2-6 years of experience in Data Engineering, Data Science, or AI
- Strong proficiency in Python
- Experience with machine learning frameworks (TensorFlow, PyTorch, Scikit-learn)
- Experience building data pipelines and processing workflows
- Strong SQL and database system knowledge
- Experience with APIs, microservices, and production deployment
- Familiarity with Git, CI/CD pipelines, and testing frameworks
- Strong debugging and problem-solving skills
Preferred Skills
- Experience with LLMs, NLP, or Generative AI
- Familiarity with MLOps tools and model deployment
- Cloud platform experience (AWS, GCP, Azure)
- Knowledge of vector databases and embeddings
- Experience with data platforms (Spark, Airflow, Kafka)
What We Look For
- Ownership: You take end-to-end responsibility for AI features
- Production mindset: You write production-ready code, not just notebooks
- Growth orientation: You learn continuously in the fast-moving AI space
- Collaboration: You work well with product and engineering teams
- Quality focus: You prioritize testing and code quality
Reporting To
Engineering Manager 
