Backend AI Engineer (Founding Team)

ABOUT US While the world races to automate the future, we’re focused on preparing the generation that will lead it.

At ADIIVA, we believe the most powerful time to shape a child’s mind is early on, when curiosity is boundless and values are just beginning to form. We offer parents a way to nurture critical thinking, resilience and independence from the very start. With our first office in Bangalore, we are looking to hire a Backend AI Developer that will help us build a revolutionary product that transforms how children learn.

ABOUT THE ROLE

We’re hiring a senior backend engineer with deep experience building scalable backend systems and deploying production-grade conversational AI. You will design infrastructure that supports millions of concurrent users while powering intelligent, reliable, low-latency conversational experiences. This is a systems-heavy role with real AI ownership This role offers unparalleled autonomy and the chance to co-create a category-defining AI device for children in a 0→1 environment. This is a full time opportunity based in Bengaluru (on-site).

WHAT YOU WILL DO

Scalable Backend Architecture Design the system architecture, covering cloud services, databases, and DevOps workflows specifically optimized for AI agent operations and large language model integration Design distributed systems handling high concurrency (100k–1M+ users) Build multithreaded, asynchronous, and event-driven architectures Develop resilient APIs with low latency and high availability Implement caching, rate limiting, queue systems, and load balancing

Conversational AI Systems (Core Requirement) Design and deploy conversational AI systems in production Build dialogue management systems (context tracking, memory, state handling) Implement conversation orchestration and model routing logic Optimize response latency for real-time conversational flows Handle fallback strategies, guardrails, and failure modes Design scalable session management for millions of conversations Work with LLM-based systems (prompt engineering, retrieval augmentation, response evaluation) Implement safety layers, moderation, and child-safe conversational constraints (if applicable)

AI & ML Infrastructure Build scalable real-time inference pipelines Deploy and monitor ML models in containerized environments Optimize inference cost, latency, and resource usage Implement evaluation frameworks and automated testing for conversational quality Handle fallback strategies, retries, and failure modes for AI systems Manage GPU/accelerator workloads where required

Observability & Debugging Implement structured logging with traceability across distributed services Design dashboards for system health and conversation analytics with alerts for fast root cause analysis Monitor model drift and conversational performance metrics

WHAT WE LOOK FOR Bachelor’s degree in Computer Science, or an equivalent discipline Ability to work independently in a fast-paced, ambiguous early-stage environment Growth mindset, strong communication skills and a collaborative spirit 5+ years of backend engineering experience, with 2+ years focused on LLMs Strong understanding of concurrency & multithreading, distributed systems, high throughput architectures, real time system design Hands on experience with conversational AI frameworks, state management Deep understanding of transformer architectures, attention mechanisms and generative models Strong Python skills with experience in PyTorch, Hugging Face, TensorFlow, Weights & Biases Familiarity with LLM orchestration frameworks ( LangGraph, LangChain, or Haystack) Experience with cloud platforms (AWS, GCP, or Azure) and their AI/ML services Comfort with MLOps tooling, containerization (Docker) and orchestration (Kubernetes, Airflow) Knowledge of RAG and vector databases (e.g., FAISS, Weaviate) Ability to explain complex AI concepts to non-technical stakeholders Passion for building safe, magical AI experiences for children and families

Bonus Experience building conversational AI for children or safety-sensitive domains Experience optimizing token usage and inference cost Experience with voice-based conversational systems Experience building AI guardrails and safety layers

Write to tellmemore@adiiva.com to apply