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Everyone builds up knowledge and experience that could help someone else, but very little of it ever leaves their head. When theyre busy, asleep or just not in the room, the people who need it are left waiting.

TwinCafe, by Viven, gives everyone a digital twin to close that gap. A twin carries a persons expertise and way of speaking, so it can talk with others for them, even about questions theyve never been asked before. It draws only on what its owner has taught it, and when a question falls outside that, it hands the conversation back to them.

Educators, lawyers, coaches, recruiters, job seekers and creators use twins to stay reachable for students, clients and audiences, on the web, on mobile and on their own sites. Owners decide what their twin knows and can change it whenever they like.

Most AI products help people get more done. Were building one that helps people share who they are.

Role Overview

Were hiring Applied AI Engineers to turn cutting-edge AI features in our digital twins into polished, production-ready experiences that people use every day. In this role, youll own AI features end to end, building using various techniques in applied AI (agentic execution, memory, context management, voice agents, and more) and fundamental techniques in software and product engineering.

Though youll collaborate closely with our AI research engineers, this role is engineering-first. Were looking for builders who have independently shipped meaningful AI products, make sound technical tradeoffs, and use modern AI development tools to move quickly without sacrificing quality.

What Youll Work On

At TwinCafe, were building digital twins that can deeply understand people, faithfully represent how they think, and create entirely recent ways for humans to interact with AI and each other. Were tackling hard problems across agent systems, memory and personalization, and AI-native consumer experiences. As an Applied AI Engineer, youll bring these capabilities to life by building:

- Intelligent Agents Conversations:



Build AI agents that interact naturally on behalf of people, from conversational onboarding and twin conversations to group chats, tool use, and third-party integrations.
- Real-Time Multimodal Experiences: Bring digital twins to life through low-latency voice agents, interactive avatars, generative UI, and immersive conversational experiences.
- Memory, Search Personalization: Build the systems that make twins more knowledgeable and personalized, including knowledge ingestion, retrieval, long-term memory, personalized feeds, and intelligent recommendations.
- Production AI Systems: Turn promising AI research into reliable, scalable products through evaluation pipelines, observability, model optimization, and improvements to latency, cost, and quality.

Must-Haves

- Production software engineering: Strong experience building, testing, deploying, and operating backend systems, APIs, and data pipelines. Able to turn experimental code into maintainable, observable production services.
- AI product ownership: Has independently shipped at least one meaningful AI-powered feature or product, and can own implementation, UX tradeoffs, launch, and iteration with limited oversight.
- Practical agentic AI: Hands-on fluency with LLM APIs and modern agent patterns, including context engineering, tool use, retrieval, memory, and structured outputs. Understands model capabilities and where simpler approaches are better.
- Technical judgment AI-native workflow: Keeps up with modern applied AI, chooses pragmatic approaches, and uses agentic coding tools effectively.



Combines strong engineering fundamentals with product taste and a bias to ship.

Nice-to-Haves

- Evaluation optimization: Experience testing AI behavior, creating practical eval datasets or graders, tracing failures, and making evidence-based tradeoffs among quality, latency, cost, and reliability.
- Real-time multimodal AI: Experience building voice agents, speech systems, interactive avatars, or low-latency multimodal applications.
- Personalization memory: Experience with long-term, pairwise, or multi-agent memory, user modeling, knowledge extraction, or systems that learn from interactions.
- Search recommendations: Experience with vector/semantic search, retrieval and reranking, feed ranking, or recommendation systems.
- Startup consumer product experience: Experience at an early-stage AI startup, building consumer products from scratch, or owning high-velocity 0-to-1 and 1-to-10 launches.

Were not expecting you to have all of the above skillsets. If youve shipped real AI products and learn rapid, we want to hear from you.

Equal Opportunity Employment:

TwinCafe is committed to equal employment opportunity and non-discrimination for all employees and qualified applicants. We value diversity and are dedicated to fostering an inclusive environment for all employees, regardless of race, color, sex, gender identity or expression, age, religion, national origin, ancestry, citizenship, disability, military or veteran status, genetic information, sexual orientation, marital status, or any other characteristic protected under applicable law.

If you are passionate about AI and eager to make an impact, we would love to hear from you.

Apply today to join the TwinCafe team and help us build the future of AI.

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Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Applied AI Engineer (Bengaluru)
🏢 Viven
📍 Bengaluru