Job highlights

- Build streaming and batch ingestion pipelines that capture events from Convogent conversations,Velogent process runs,and customer systems of record - with idempotency,ordering,and replay support. . .

You will build the storage and retrieval backbone of Aiva: the context graph itself, the ingestion pipelines that populate it, and the query layer that serves it to agents in real time. This is a deep backend role for an engineer who cares about data modeling, query performance, and correctness under scale - and who wants their work to sit on the critical path of every agent interaction across the Aivar platform.

Key Responsibilities

- Implement the context graph data layer: schema, entity and relationship management, versioning, and time-aware (temporal) memory records.

- Build streaming and batch ingestion pipelines that capture events from Convogent conversations, Velogent process runs, and customer systems of record - with idempotency, ordering, and replay support.

- Develop entity resolution and deduplication: matching customers, accounts, and interactions across channels into a single coherent graph identity.

- Implement the hybrid retrieval service - graph traversal, vector k-NN, and metadata filtering - with caching, pagination, and strict latency budgets.

- Build and maintain Aivas public APIs and internal SDKs (REST/gRPC, and MCP-compatible tool surfaces) with robust authentication, rate limiting, and multi-tenant scoping.

- Own performance engineering: query profiling, index design, load testing, and capacity/cost tuning across graph and vector stores.

- Implement data lifecycle mechanics: TTL and decay policies, archival,



tenant-scoped deletion (right-to-be-forgotten), and audit logging in line with AI Gateway governance policies.

- Write thorough tests, runbooks, and operational dashboards; participate in on-call for the platform.

Must-Have Qualifications

- 6+ years of backend engineering in Python, Go, or Java/Kotlin, building services in production at meaningful scale.

- Hands-on production experience with at least one graph database (Neptune, Neo4j, ArangoDB) or a demonstrated ability to model highly connected data in relational/NoSQL stores.

- Practical experience with search/vector retrieval: OpenSearch/Elasticsearch, pgvector, or a dedicated vector database, including index tuning and relevance debugging.

- Solid data pipeline skills: Kafka/Kinesis or equivalent, exactly-once/idempotent processing patterns, and schema evolution.

- Solid AWS experience (EKS or Lambda, DynamoDB, S3, IAM) and infrastructure-as-code (Terraform/CDK).

- Rigor around API design, testing, observability (metrics, tracing), and secure multi-tenant service patterns.

Nice-to-Have

- Experience with entity resolution, identity graphs, CDPs, or master data management.

- Exposure to RAG systems or LLM-serving infrastructure.

- Familiarity with Gremlin/openCypher/SPARQL query languages.

- Experience meeting compliance requirements (data residency, PII handling) in BFSI, healthcare, or telecom.

Disclaimer: This has been sourced from a public domain and may have been modified by Naukri.com to improve clarity for our users. We encourage job seekers to verify all details directly with the employer via their official channels before applying.

📌 Senior Software Engineer - Knowledge Graph & Retrieval (Aiva) (Coimbatore)
🏢 Aivar Innovations
📍 Coimbatore