AI / Data Architect

Tango is a successful, market leader, a live-streaming Platform with 450+ million registered users, in an industry projected to reach $240 BILLION in the next couple of years. 

The B2C platform, based on the best-quality global video technology, allows millions of talented people around the world to create their own live content, engage with their fans, and monetize their talents.

Tango live stream was founded in 2018 and is powered by 500+ global employees operating in a culture of growth, learning, and success!

The Tango team is a vigorous cocktail of hard workers, creative brains, energizers, geeks, overachievers, athletes, and more. We push the limits to bring our app from “one of the top” to “the leader”. 

The best way to describe Tango's work style is not to use the word “impossible”. We believe that success is a thorny path that runs on sleepless nights, corporate parties, tough releases, and, of course, our users' smiles (and as we are a LIVE app, we truly get to see our users all around the world smiling right in front of us in real-time!). 

Do you want to join the party?

Responsibilities

• Architect and Evolve Data Infrastructure- Design and implement scalable data pipelines, Data Lakes, and Data Warehouses to support analytics, AI, and product intelligence.
• Build and Deploy AI-Powered Systems- Operationalize AI/ML models- from prototyping to production-grade inference- ensuring performance, monitoring, and reliability.
• Enable BI and Analytics- Collaborate with business and product teams to turn raw data into actionable insights, visualizations, and predictive metrics.
• Ensure Data Quality and Governance- Establish standards for data collection, validation, lineage, and retention.
• Leverage LLMs and AI APIs- Integrate modern large language models and external AI services for chatbots, insights generation, and automation use cases.
• Collaborate Across Teams- Work closely with engineers, ML specialists, and product stakeholders to align data and AI architecture with business goals.

Requirements

• 8–10+ years of experience in software, data, and/or AI systems architecture.
• Proven experience designing and implementing data pipelines, ETL/ELT workflows, Data Lakes, and Data Warehouses.
• Strong hands-on expertise with SQL and NoSQL databases.
• Solid understanding of distributed systems and client-server architectures.
• Understanding of real-time analytics and stream-processing architectures.
• Experience deploying AI/ML models to production (wrapping inference services, monitoring performance).
• Knowledge of streaming systems (Kafka, Pub/Sub) and workflow orchestration tools (Airflow, etc.).
• Experience integrating LLMs or AI APIs into production products (chatbots, embeddings, recommendations).
• Strong grasp of cloud environments (GCP, DigitalOcean, AWS, etc.) and container orchestration (Docker, Kubernetes).
• Experience with BI/analytics workflows (e.g., BigQuery, Looker).
• Excellent communication skills and proficiency in English (Intermediate+).

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