Forward Deployed Engineer

Location: Bengaluru On-site
Experience: 05 Years
Job Type: Full-time
Level: Individual Contributor
Travel: No travel required
Reporting To: Founders / Leadership

About us

YoYo AI helps retail brands understand what is actually happening on their shop floors. Our devices capture conversations between customers and sales staff. Our AI reads those conversations and picks out the things that decide whether a sale happens: what the customer came in for, what they hesitated over, where the pitch fell short. Sales leaders, marketers, category buyers and L&D teams then use that to make calls they were earlier making on instinct.

We work with brands in jewellery, apparel, electronics, furniture, auto, home improvement, hospitality and BFSI. We are building this out of Bengaluru, for India and for markets beyond it.

The role

A working product and a working deployment are two different things. You are the person who closes that gap.

You sit inside the client's head office. You get the deployment live, you get their teams using the dashboards, and you own whether the AI is returning something worth acting on. Every client is different: different languages on the floor, different store noise, different vocabulary for the same product, different CRM, different idea of what a good conversation looks like. The core platform does not change for each of them. You are the layer that makes it fit, and you are the one the client meets.

You are encouraged to spend time in stores. The engineers who do the best work here are the ones who have stood on a shop floor and watched where the pitch and the pipeline actually break. Nobody will make you go. You will also spend real time in the codebase, because you fix what you find rather than filing it.

What you build has a commercial edge to it. A pilot converts when the client sees the result they were promised, and an account grows when a second team inside it sees what is already sitting in their data. Both of those outcomes are yours to deliver, not somebody else's to chase.

What you will do

• Own the deployment end to end. Device provisioning, store connectivity, data flowing, first insight in front of the client. Get from kickoff to something real inside the pilot window, and know by the halfway mark whether it is in trouble.
• Get their HQ using it. A dashboard nobody opens is a failed deployment. Sit with the sales, marketing and L&D teams, show them what is in their own data, and make sure the people who asked for this are actually looking at it every week.
• Make the AI work on their floor. Their languages, their store noise, their product vocabulary. Benchmark transcription and speaker separation on their actual audio, and fix what fails instead of explaining it away.
• Build the vertical. Intent taxonomies, objection maps and prompt libraries for the category you are deployed into. A jewellery floor and an electronics floor do not share a conversation model.
• Wire it into their systems. CRM and POS integrations, so conversation data connects to what actually got sold and the insight can be checked against reality.
• Build what the client asks for. Custom reports, dashboards and agents. Ground everything in source conversations and verify it before it ships, because a confident wrong number costs an account.
• Close the pilot. A pilot converts on results, not on effort. Know what the client agreed to judge this on, work backwards from it, and make sure the output in front of their leadership at the end is the thing they asked for.
• Grow the account. The same intelligence is worth something to marketing, L&D and category teams inside the same client. Spot which of them would benefit, show
• them what is already in their data, and hand a real opening to the account team.
• Push it back into the product. Turn one-off client work into something the platform does by default, so the next deployment starts further ahead than this one did.

What we are looking for

Must have

• 0 to 5 years of experience. A consulting internship or an analyst role is the closest match to what this job actually asks for, but we care more about what you can do than where you did it
• Coding ability, ideally Python. Degree, internship, first job or your own projects. What we want to see is something you built that other people actually used
• Excel or Sheets at a real working level. A lot of the first conversation with a client happens in a spreadsheet before it ever happens in a dashboard
• The ability to explain a complicated idea simply. You will be taking AI output to people who do not think about models, and the explanation matters as much as the result
• Comfort at the boundaries. APIs, data pipelines, some frontend, some hardware when a device misbehaves
• An eye for where a deployment turns into more business, and the willingness to raise it yourself
• Heavy hands-on LLM usage. Prompts, evaluations, retrieval, and a clear view on where these tools break
• Fluent English and Hindi. A third Indian language counts for a lot, since the useful conversations happen on store floors and not only in HQ meeting rooms
• The instinct to go and find out what a client needs rather than waiting to be told

Good to have

• Speech or audio work. Transcription, diarization, voice activity detection, or anything that survives noisy real-world recording
• Embedded or IoT experience, on ESP32 or similar
• SQL and experience building things customers actually look at
• Side projects, hackathons or internships where you shipped without a spec and it worked