🎁 Zanim zaaplikujesz, przećwicz tę rozmowę. Załóż darmowe konto WorkMundi i odbierz Trening rozmowy kwalifikacyjnej w HelpsYouSpeak — bez opłat, bez karty. Chcę swój trening →
Description 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 Own and grow our internal AI agent tooling - skills, agents, CI/CD pipelines, and the deployment tooling that ships changes safely to production. Build and deploy LLM-based AI agents (data modeling, semantic layer, data quality, and validation checks) in a secure, reproducible multi-agent environment with access to our data warehouse and internal tools. Develop and maintain reusable AI skills that let an AI assistant answer business questions accurately against our data warehouse. Investigate and evaluate new approaches - RAG pipelines, vector databases, alternative model providers, self-hosted agent infrastructure - and bring the best ones into production. Support domain teams in data modeling - helping analysts and data engineers build semantic layers, canonical schemas, and AI test/eval question sets so their data is AI-ready. Troubleshoot MCP (Model Context Protocol) integrations end-to-end - connectivity, auth/IAM, tool schemas, and degraded or failing tool calls. Own the reliability and accuracy of deployed agents - monitoring, eval tracking, incident response, and iterating based on real usage. Requirements Must-have 3+ years of experience as an AI/ML Engineer, Data Engineer, or Software Engineer building production systems with LLMs. Hands-on experience building agents or applications with Claude, GPT, or similar LLM APIs; solid understanding of RAG architectures and vector databases. Strong Python and SQL skills, and comfort working with data models and cloud data warehouses. Strong communication skills - able to work directly with non-engineering stakeholders and explain technical concepts clearly. Ability to work in a fast-paced environment: comfortable investigating unproven tools and making pragmatic build-vs-adopt calls. English level: professional working proficiency (B2+). Nice-to-have Experience with data-quality frameworks (e.g., Soda). Experience with workflow orchestration (e.g., Airflow) and CI/CD pipelines. Prior work on internal developer tooling, platform engineering, or AI agent infrastructure. Experience running or contributing to multi-agent systems. What we offer: Stock options grant (we’re a Silicon Valley Company) Competitive salary Hybrid flexibility 4 days in office 1 home office Medical insurance for you and 75% off for your relatives Lunch budget Parking Multisport card Cheerful team spirit and fun office atmosphere If this sounds like you, apply and help empower live entertainers and creators to build independent businesses around their live talents.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.