Java Fullstack Engineer

About QUIPUQuipu is AI infrastructure for long-term memory, built for enterprises engineering complex systems—automotive, drug development, battery storage, and AI agents. We give every entity a single, audit-grade memory so teams can study cause and effect rather than guess at it.That means vehicles with component-level traceability and failure prediction, accelerated drug development with fewer risky experiments, battery systems with trusted cell-ageing models, and agents with a shared persona that never resets.Working Model — please read before applyingThis is an on-site role at T-Hub, Hyderabad, on a 6-day working week for the first 9 months. We're building core infrastructure to a hard timeline, and we'd rather be upfront about the commitment than surprise you later. After the initial 9 months, the schedule moves to a standard 5-day week.The RoleA Java backend engineer who thinks in systems, not just code. You'll own architecture decisions on core platform services—distributed microservices that handle graph storage, streaming ingestion, ETL pipelines, and semantic retrieval at scale—and you'll be expected to reason about trade-offs and failure modes before writing a line of code.Experience required: 2–5 years of professional Java backend development. Applications with less than 2 years of professional experience will not be considered.What You'll Do•     Build and maintain Spring Boot microservices that form the core of a distributed graph memory platform•     Own product architecture decisions: service boundaries, data flow, failure handling, and evolution of the platform as it scales•     Design and implement security and access control in Java—authentication, authorization, multi-tenant data isolation, and secrets management (Keycloak, Vault, or comparable)•     Work with event-driven and streaming architectures—Kafka-based pipelines, backpressure-aware stream processing, and actor-model concurrency•     Build and operate ETL and data ingestion workflows: extraction, transformation, validation, and loading across heterogeneous sources•     Model and query data across polyglot persistence: graph databases (Neo4j), distributed SQL (YugabyteDB), vector stores, and embedded key-value stores•     Own features end-to-end: design, implementation, testing, deployment, and production debugging•     Debug issues across the stack using logs, metrics, and traces•     Participate in design reviews and explain your technical decisions with clear reasoningMust-Have Skills•     2–5 years of professional experience with Java and Spring Boot in production•     Solid grounding in core Java: collections, concurrency, JVM fundamentals•     Product architecture experience: designing service boundaries, reasoning about trade-offs, and owning systems beyond individual features•     Working knowledge of security and access control in Java applications: authentication/authorization flows (OAuth2/OIDC, JWT), role- and attribute-based access control, and secure API design•     Hands-on production experience with Kafka or comparable event-streaming platforms•     Experience building or operating ETL / data pipeline processes•     Solid grasp of distributed systems fundamentals: consistency models, partitioning, idempotency, retries, backpressure, and failure handling•     Strong SQL skills and familiarity with at least one relational database•     Experience with at least one NoSQL or graph database•     Comfort reading logs, metrics, and traces to find root causes in running services•     Ability to reason about a system before coding it—design rationale, not just working code•     Available to work on-site in Hyderabad, 6 days a week for the first 9 monthsStrong Plus•     Keycloak, HashiCorp Vault, or hands-on IAM integration in production•     Experience with Akka or Apache Pekko (actors, streams, cluster)•     Graph databases (Neo4j, Cypher) or graph data modeling•     Distributed SQL databases (YugabyteDB, CockroachDB, Spanner-class systems)•     Vector databases and semantic search pipelines (Milvus, pgvector, etc.)•     Python (FastAPI) for building service sidecars•     Exposure to LLM-integrated systems: prompt pipelines, extraction workflows, RAG architectures•     Infrastructure familiarity: Jenkins, Docker, containerized deployments on LinuxWho You Are•     You ask, "Why is the system shaped this way?" before asking, "What do I build?"•     You're comfortable with ambiguity and small-team ownership—no hand-holding, no rigid specs•     You debug from first principles and write down what you learn•     You communicate trade-offs clearly and can disagree constructively in design discussionsWhat We Offer•     Direct ownership of core infrastructure on a small team—your work ships and matters immediately•     Deep, unusual technical problems: bitemporal modeling, graph traversal at scale, streaming knowledge extraction•     Close mentorship from technical leadership on architecture and systems design