Senior Backend Engineer | Founding Team

Job descriptionTitle : Senior Backend Engineer | Founding TeamLocation: Bengaluru / HybridExperience: 6–10 yearsType: Full-time | Founding Team | About DecisionXwww.decisionx.aiWe’re building a Self-Learning, Context-Aware Decision AI — one that uses Ontology, Context, and AI Agents to reimagine how humans and organisations make complex decisions. Our platform learns continuously, understands intent, and reasons across information — bringing clarity to the moments that matter most.We’re a small team of serial founders, engineers, physicists, product artists, and builders who believe:“The future will be shaped not by those with the most data, but by those who decide best.”Our mission is bold yet simple — to build the last piece of Decision Intelligence humanity will ever need, empowering better choices for today’s world and for the futures yet to come.Headquartered in Bangalore and San Francisco, DecisionX is led by a global team advancing the next frontier of Reasoning and Decision AI.What You'll BuildData BackboneETL/ELT pipelines for structured/unstructured data from ERP, APIs, warehouses, filesData models for time-series, hierarchical dimensions, multi-billion row aggregationsOLAP query layers: sub-second performance on complex analyticsStreaming/batch ingestion with exactly-once semanticsTech: ClickHouse, Druid, Snowflake, BigQuery, Redshift, Airflow, KafkaBackend & APIsMicroservices architecture with clean boundaries and fault isolationRESTful/GraphQL APIs that are simple to use, impossible to misuseAsync processing, job orchestration, distributed workflowsHigh availability, horizontal scale, graceful degradationTech: Python/Java/Go, Celery, Temporal, RabbitMQ, Redis, KubernetesAgent OrchestrationMulti-step agent workflows: goal decomposition, task coordination, learning loopsStateful execution engines tracking decision context across sessionsReasoning loops where agents query, simulate, and update plans autonomouslyAbstractions for LLMs, analytical models, optimization solversError recovery, retries, human-in-the-loop patternsNumerical Analytics at ScaleHigh-volume, high-dimensional datasets: sales, financials, operational KPIsAggregation engines for dashboards, anomaly detection, RCAQuery optimization: indexing, materialized views, pre-aggregation, cachingStatistical/ML analytics: forecasting, outlier detection, correlation analysisNumerical accuracy and consistency in distributed systemsYou Must HaveBackend:6–10 years building distributed systems in productionExpert in Python, Java, or GoMicroservices, API design, async processing (Celery, Kafka, RabbitMQ)Distributed systems: consistency, partitioning, replication, fault toleranceData:ETL/ELT pipelines processing millions of records dailyData warehouses/OLAP: Snowflake, Redshift, BigQuery, ClickHouse, or DruidStrong SQL, query optimization, data modeling (star schemas, time-series)Orchestration tools: Airflow, Prefect, or DagsterQuantitative:Large-scale numerical datasets: financials, metrics, time-seriesAggregation strategies, rollups, pre-computationNumerical precision and correctness in distributed systemsInfrastructure:AWS, GCP, or Azure in productionDocker, CI/CD, infrastructure-as-codeMonitoring/logging/alerting: Prometheus, Grafana, DatadogMindset:You've debugged distributed systems at 3 AM and shipped the fixYou understand trade-offs: ClickHouse vs. Snowflake, when to denormalize, when to cacheYou write code other engineers want to readBonus:Worked in the domain of BI platforms, dashboards, analytics engines beforeAgentic AI, LLM orchestration, reasoning workflows excite you Startup/founding team experience in the past Why JoinFounding Team: Meaningful equity, outsized influence on architecture and culture, direct founder collaboration.Technical Leverage: Build systems powering Fortune 500 decision-making. Deep technical work = defensible moats.Domain: Enterprise decision intelligence is infrastructure, not a feature. You'll work at the intersection of distributed systems, data engineering, agentic AI, and decision science.Ownership: This isn't a job. It's a chance to build something that matters and own a piece of it.