Overview
You will be one of the first core engineers building an AI platform that lets vendors rapidly create and deploy conversational AI agents (avatars, chat, voice) across websites, LinkedIn, email, and more. The product is in MVP with ~7 microservices in production; you will extend and harden the platform, design new services, and work on cutting-edge AI/agent capabilities. **What We’re Looking For (Mindset)** “Builder” mentality: you think in terms of systems, not just individual tickets Very comfortable using and embracing AI to move faster and build better software Hands-on, pragmatic, and willing to “get your hands dirty” with new tech Long-term commitment: interested in joining a small team and growing with it
Key responsibilities
- Design, develop, and maintain Kotlin/Spring Boot microservices on JVM
- Build and evolve the AI engine and agent orchestration (conversational agents, avatars, chat, voice)
- Implement and optimize RAG pipelines (semantic, lexical, and knowledge-graph based)
- Integrate and experiment with LLMs (Gemini, open-source/Hugging Face, etc.)
- Work on infrastructure-level pieces (new microservices, internal tooling, web agents, observability, performance)
- Use AI tools (Claude, Copilot/Codex, etc.) throughout the development lifecycle (design, coding, code review)
- Collaborate with product/UX on requirements and translate them into robust, scalable systems
- Participate in architecture, design reviews, and technical decision-making
Required experience
- Strong professional experience with Kotlin on the JVM
- Solid hands-on experience with Spring Boot microservices
- Deep understanding of system design, distributed systems, and cloud architectures (preferably GCP)
- Experience building production-grade backend services (clean code, testing, observability, performance)
- Comfortable working with databases and caching (e.g., MongoDB, Redis)
- Familiarity with LLMs and AI development workflows (prompting, evaluation, integration)
- Experience building with any agentic frameworks (e.g., LangChain, LangGraph, CrewAI, AutoGen)
- Proven ability to use AI tools (e.g., Claude) as part of the development process, including AI-assisted code review
- Strong ownership, proactivity, and ability to deliver in a fast-paced environment
Bonus points
- Experience with: Neo4j or other graph databases Vector databases / semantic search (e.g., MongoDB Atlas Search, other vector stores) Hybrid RAG systems (lexical + semantic + knowledge graph) LangGraph4J
- Building web agents / browser-based autonomous agents
- Background in AI/ML, NLP, or information retrieval
- Exposure to UX / frontend; ability to collaborate closely with product/UX
To apply
Send your CV, a snappy cover letter which highlights your expertise, skills and experience and any relevant links/attachments to your work.
Have questions?Write to us