AI Platform Engineer

We are looking for an AI Platform Engineer with 4+yrs of experience, to design and build the foundational platform that enables scalable, reliable, and self-service data and AI workflows.

This role focuses on platform thinking over one-off solutions building systems that other engineers and teams can use independently.

What You Will Work On

Design systems that support increasing data volume and concurrent workloads without re-architecture

- Platform Design: Standardized infrastructure for all data and AI workloads
- Self-Service: Teams can build and access data independently
- Scalability: Systems that grow without constant rework
- Reliability: Stable, observable, and governed data systems

Your Responsibilities

- Data Platform Architecture
- Design and build a centralized data platform (batch + streaming if needed)
- Define standards for ingestion, transformation, and storage
- Eliminate duplicated and siloed pipelines
- Orchestration & Workflow Systems
- Build and manage orchestration frameworks (e.g., Airflow, Prefect)
- Standardize how pipelines are scheduled, monitored, and retried

- Enable reusable pipeline templates
- Data Access & Developer Experience
- Build self-service data access layers (APIs, query engines, semantic layers)
- Improve developer experience for data teams (tooling, abstractions)
- Enable fast and reliable data consumption

- Platform for AI/ML Workloads
- Provide infrastructure for training, experimentation, and deployment
- Enable reproducibility and versioning of data and models
- Support integration between data platform and ML systems
- Reliability, Governance & Observability
- Implement logging, monitoring, and alerting across the platform




- Define SLAs for pipelines and platform services
- Enforce access control, security, and data governance
- Align platform capabilities with business and data use cases
- Data as a Product (Platform Level)
- Standardize how datasets are created, documented, and shared
- Enable discoverability and reuse across teams
- Treat data assets as long-lived, versioned products

To succeed, you will need:

- Bachelors or master’s degree or equivalent practical experience
- 4+ years in data platform, backend, or infrastructure engineering
- Strong experience in data platform or infrastructure engineering
- Experience designing scalable distributed systems
- Deep understanding of data pipelines, storage systems, and APIs

Technical Expertise:
- Cloud platforms (AWS, GCP, Azure)
- Orchestration tools (Airflow, Prefect, Dagster)
- Data technologies (Spark, Kafka, warehouses like Snowflake/BigQuery)
- Infrastructure as Code (Terraform or similar)

Nice to Have

- Exposure to the product development lifecycle
- Experience working in agile product teams (Scrum, Kanban, etc.)
- Experience building internal platforms/tools
- Experience with data observability tools
- Experience supporting ML/AI workflows in production
- Experience with embeddings / vector search /Knowledge Graph

Why Join Us

- Work on central enterprise systems with real business impact
- Modern technology stack and forward-looking architecture
- Strong engineering culture with high autonomy and ownership
- Opportunity to shape AI supported software development practices.
- Hybrid working model with remote options across the EU.
- Collaborative, international setting centered on technical excellence.

Job location Pune, Pimpri Chinchwad

📌 AI Platform Engineer - 4+yrs (Pune)
🏢 Techprimelab
📍 Pune