Software Engineer - AI Products

What You’ll Do

• Design and build backend systems that power real-time, low-latency AI experiences

• Architect and implement agentic AI flows: tool calling, multi-step reasoning, orchestration, memory, and planning

• Build and evolve conversational AI systems: dialogue management, context handling, intent routing, fallback design

• Own the infra behind AI features: streaming responses, WebSocket/SSE pipelines, queue-based orchestration

• Make product-level decisions: you’ll have opinions on what to build, not just how to build it

• Work on voice-enabled systems (STT/TTS, streaming APIs) as part of end-user experiences

• Deploy and operate services with a focus on low latency, high availability, and robustness

• Instrument, monitor, and improve AI systems in production (eval frameworks, latency tracking, cost optimization)

What We’re Looking For

Must Have:

• 1- 4 years of backend and AI engineering experience. 

• Strong proficiency in Python

• Hands-on experience building with LLMs: prompt engineering, function/tool calling, RAG, embeddings, fine-tuning awareness

• Experience with agentic AI patterns: multi-agent orchestration, ReAct loops, planner-executor architectures, or similar

• Strong fundamentals in real-time systems

• Keen interest in building AI-driven products, particularly voice and conversational experiences

• Strong systems design instincts, with a practical mindset for navigating technical tradeoffs

• Product thinking: you understand why you’re building something, not just the ticket description

• Comfort with ambiguity: AI product development is fast, iterative, and occasionally chaotic

Strong Signals

• Built or shipped AI products (voice or text chatbots, copilots, assistants)

• Experience designing evaluation and feedback loops for AI systems

• Contributed to or built open source developer tools, SDKs, or internal platforms

Bonus

• Experience with voice AI / speech-to-text / text-to-speech pipelines

• Background in distributed systems, message queues (Kafka, RabbitMQ, Redis Streams)

• Exposure to on-device or edge AI inference

• Open-source contributions in the AI/ML space
   

Tech You’ll Likely Touch

LLMs (OpenAI, Anthropic, open-source models), Python/Node.js, Redis, PostgreSQL, WebSockets / SSE, Docker, Kubernetes, vector databases, CI/CD pipelines, observability tools.

What We Value

• Ownership — you see a problem, you fix it. You don’t wait for a spec.

• Speed with taste — ship fast, but ship something you’d want to use yourself.

• Clear thinking — you can explain a complex system in simple terms.

• Curiosity — the AI landscape moves weekly. You keep up because you want to, not because you have to.

Candidates are responsible for safeguarding sensitive company data against unauthorized access, use, or disclosure, and for reporting any suspected security incidents in line with the organization's ISMS (Information Security Management System) policies and procedures.