We’re hiring a Database Developer / Lead Database Engineer at Avathon – where AI meets the real world.
This is a high-impact role at the intersection of low-level systems programming, distributed storage, and query engine optimization, focused on building core database technology ground-up rather than application-level software.
We are looking for an experienced Database Engineer to lead the architecture, design, and deployment of engine-level database systems across high-performance, large-scale environments. You will tackle real-world storage challenges involving distributed consensus, transaction isolation, custom indexing, and high-throughput query processing across multi-model architectures.
This role offers the opportunity to drive innovation in storage engine design, graph processing, distributed execution, and system reliability, while collaborating closely with engineering and product teams to bring resilient, production-grade database systems into reality.
Core Responsibilities
Architecture & Engine Design
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Storage Engines: Design and implement storage layers using LSM Trees, B-Trees, RocksDB, LevelDB, LMDB, WiredTiger, or custom engines.
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Storage & Indexing: Build efficient key-value storage layouts, secondary/composite indexes, inverted indexes, spatial indexes, and vector indexes.
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Data Iteration: Design high-throughput pagination, cursor mechanics, and large-scale dataset iteration patterns.
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Performance Tuning: Optimize write/read amplification, compaction strategies, caching layers, and Bloom filters.
Distributed Systems & Reliability
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Consensus & Sharding: Implement Raft or Paxos consensus, data partitioning/sharding strategies, and multi-node replication.
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Fault Tolerance: Architect resilient systems capable of automated leader election, failure recovery, dynamic retries, and partition handling.
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Platform Operations: Integrate service discovery (etcd, Consul, ZooKeeper), distributed tracing/observability, zero-downtime rolling upgrades, back-ups, and storage format compatibility layers.
Concurrency, Transactions & Query Execution
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Transaction Control: Work with MVCC, Snapshot Isolation, Optimistic Concurrency Control (OCC), and Two-Phase Locking (2PL).
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Crash Recovery: Implement WAL (Write-Ahead Logging), crash recovery guarantees, deadlock detection, and distributed transactions (2PC).
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Query Optimization: Build and optimize query execution plans, join algorithms, predicate pushdowns, and distributed query execution pipelines.
Quality, Testing & Systems Engineering
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Low-Level Development: Write production-grade C++17/20, Rust, Java, or Scala code focused on low-overhead memory management, profiling, and benchmarking.
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Validation & Testing: Ensure transactional correctness and data integrity via distributed fault injection, property-based testing, and consistency validation suites.
Technical Qualifications
Graph Database Experience (Highly Preferred)
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Hands-on experience with JanusGraph/Titan, Neo4j, TigerGraph, Amazon Neptune, Dgraph, or a custom in-house graph engine.
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Strong understanding of graph storage models, traversal algorithms, graph indexing, and distributed graph processing.
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Familiarity with graph query languages such as Gremlin, Cypher, SPARQL, or SQL/PGQ.
Specialized Indexing
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Vector Search: HNSW, IVF, ANN techniques.
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Spatial Indexing: R-Tree, H3, S2, Geohash.
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Search & Composite: Inverted indexes, full-text search, and multi-column composite structures.
Engineering & Systems Core
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Languages: C++17/20 or Rust (systems level); Java or Scala (distributed services).
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Systems Skills: Deep experience with performance profiling, memory management, low-level debugging, and automated benchmarking.
Lead Engineer Expectations
Candidates applying for Senior or Lead designations will also be expected to:
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Lead technical design, write RFCs/design docs, and establish system architecture.
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Mentor engineers, conduct thorough code reviews, and drive technical standards.
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Deconstruct complex engine initiatives into structured milestone roadmaps.
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Spearhead production incident investigations and root-cause analysis (RCA).
