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 Engineer 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 integrationDesign distributed systems handling high concurrency (100k-1M+ users)Build multithreaded, asynchronous, and event-driven architecturesDevelop resilient APIs with low latency and high availabilityImplement caching, rate limiting, queue systems, and load balancingAI & ML Infrastructure
Build scalable real-time inference pipelinesDeploy and monitor ML models in containerized environmentsOptimize inference cost, latency, and resource usageImplement evaluation frameworks and automated testing for conversational qualityHandle fallback strategies, retries, and failure modes for AI systemsManage GPU/accelerator workloads where requiredKey Technical Skills
Inference engines: vLLM, TGI ( Text Generation Inference), NVIDIA TritonOrchestration: Kubernetes with GPU node pools, Ray Serve, BentoML Observability: Prometheus + Grafana for model metrics, latency tracking, drift detectionCost optimization: Model quantization (AWQ, GPTQ, INT8), batching strategies, auto scalingContainerization: Docker, Helm, container registries, multi-stage builds Cloud/accelerators: CUDA, experience with A100/H100 or cloud GPU instances (AWS, GCP, Azure) Reliability: Circuit breakers, retry logic, shadow deployments, canary rollouts
Observability & Debugging
Implement structured logging with traceability across distributed servicesDesign dashboards for system health and conversation analytics with alerts for fast root cause analysisMonitor model drift and conversational performance metricsWHAT WE LOOK FOR
Bachelor's degree in Computer Science, or an equivalent disciplineAbility to work independently in a fast-paced, ambiguous early-stage environmentGrowth mindset, strong communication skills and a collaborative spirit2+ years of backend engineering experience, focused on LLMsStrong understanding of concurrency & multithreading, distributed systems, high throughput architectures, real time system designHands on experience with conversational AI frameworks, state managementDeep understanding of transformer architectures, attention mechanisms and generative modelsStrong Python skills with experience in PyTorch, Hugging Face, TensorFlow, Weights & BiasesFamiliarity with LLM orchestration frameworks ( LangGraph, LangChain, or Haystack)Experience with cloud platforms (AWS, GCP, or Azure) and their AI/ML servicesComfort 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 stakeholdersPassion for building safe, magical AI experiences for children and families Read Less