About Slang AI Slang AI is redefining customer engagement through conversational AI. Our mission is to transform the restaurant industry with the ultimate voice AI solution for consistently outstanding guest experiences. Backed by Techstars.
About the role
You'll join Slang's Engineering team as our Applied AI Engineer, the person who turns foundation models into products that restaurants trust with their phones. This is not a research or model-training role. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- You will design and ship a provider-agnostic model interface for our voice and text AI, so we can run the same product on different models without rewriting prompts or business logic
- You will build an automated evaluation pipeline (offline eval sets, scenarios, production metrics) that every model and prompt change runs through before it ships, and that the rest of the team can use without you
- You will run model and prompt experiments in production with clear success metrics (booking accuracy, containment, transfer rate, caller hang-ups, latency, cost) and make recommendations the team can act on
- You will measurably reduce AI errors that matter most to restaurants, by moving critical facts into deterministic tools and guardrails rather than model memory
- You will own the latency and cost profile of our AI stack, and bring a clear point of view on when to use frontier APIs, faster inference providers, or open-weight models
- You will set the technical standards for prompt architecture, agent design, and AI observability, and document them so engineers across pods can build on them
More about this role
You'll join Slang's Engineering team as our Applied AI Engineer, the person who turns foundation models into products that restaurants trust with their phones. This is not a research or model-training role. You'll work with hosted frontier models and open-weight alternatives, and our own stack to solve real product problems: choosing the right model for each job, designing prompt architectures that hold up across model versions, wiring up agents and tool calls, and proving with evaluation that every change makes the product better before it reaches a guest. When a caller asks for a table for four on Friday at 7, you're the reason the AI gets the date right, sounds like a great host, and knows when to hand off to a human.
You'll lead the work to put model calls behind clean interfaces, redesign prompts so they travel across providers, and build the evaluation and A/B testing machinery that lets us swap models with confidence instead of hope. You'll own this loop end to end: prototype, eval design, rollout, production monitoring, and the post-launch question of "is it actually working for restaurants?" You'll partner closely with backend and platform engineers, product managers, and...
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