Principal Engineer — Aiva Platform

Aivar Innovations; Coimbatore District; On-site; INR 4,200,000 - 8,000,000; Full time

Job summary

Aivar Innovations seeks a seasoned Principal Architect to own the end‑to‑end Aiva platform architecture. You will drive data models, storage topology, and the memory lifecycle, while mentoring a lean team to deliver hardened, scalable components.

You will steer design decisions across graph, vector, and structured stores, ensuring tenancy isolation, governance, and production SLOs for diverse enterprise customers in regulated environments.

Qualifications

• 12+ years building backend/data platforms with principal ownership.

Responsibilities

• Own the Aiva platform architecture: context graph, storage topology, and memory lifecycle.
• Design hybrid retrieval layer with graph traversal, vector similarity, and filters.
• Define API/SDK surface with clear contracts, versioning, and backward compatibility.
• Architect multi-tenancy, data isolation, encryption, and residency controls for regulated customers.
• Integrate memory governance with Convogent, Velogent, and Aivar AI Gateway.
• Set production SLOs, capacity planning, and incident response.
• Hire and mentor the Aiva team; lead engineering standards and reviews.
• Represent architecture in customer/partner conversations with CXOs.

Skills

Platform architecture

Graph databases

Vector search

Distributed systems

LLM app architecture

Security/compliance

Education

Bachelor's or Master's in CS/SE

Tools

Neptune

Neo4j

OpenSearch

DynamoDB

Kafka/Kinesis

Job description

You will own the end-to-end architecture of Aiva — Aivar's memory and context graph platform — from data model to APIs to production SLOs. This is a hands‑on, code‑first principal role: you will set the technical direction, make the hard trade-offs (graph vs. vector vs. hybrid, consolidation vs. recall latency, tenancy isolation vs. cross‑agent sharing), and build the first versions of the hardest components yourself while mentoring a small, high‑leverage team. Aiva must serve three very different consumers — voice agents that need sub‑100ms context recall, long‑running process agents that need transactional state, and fine‑tuned small models that need curated training context — behind one coherent platform, governed by the Aivar AI Gateway.

Key Responsibilities

• Own the Aiva platform architecture: context graph data model (entities, relationships, episodic and semantic memory layers), storage topology, and the memory lifecycle — capture, extraction, consolidation, retrieval, decay, and deletion.
• Design and build the hybrid retrieval layer combining graph traversal, vector similarity, and structured filters, with hard latency budgets for real‑time voice(Convogent) and throughput targets for batch agentic workloads (Velogent).
• Define Aiva's API and SDK surface — including MCP-compatible interfaces — so accelerator teams and enterprise customers can read/write memory with clear contracts, versioning, and backward compatibility.
• Architect multi‑tenancy, data isolation, encryption, and residency controls suitable for regulated enterprise customers (BFSI, healthcare, telecom), including deployment into customer VPCs and sovereign/air‑gapped environments.
• Integrate memory governance with the Aivar’s Convogent, Velogent and Aivar AI Gateway and ReVAct: memory access policies, audit trails, PII redaction and consent‑aware retention, and per‑tenant observability and cost attribution.
• Set and own production SLOs (latency, recall quality, availability) and the operational model — capacity planning, cost‑per‑tenant economics, and incident response.
• Make build/buy/adopt decisions across the stack (e.g., Neptune vs. Neo4j vs. custom, OpenSearch vs. dedicated vector stores, event streaming choices) with clear written rationale.
• Hire, mentor, and technically lead the Aiva team; establish engineering standards, design review cadence, and documentation culture.
• Partner with the co‑founders on Aiva's roadmap and represent Aiva's architecture in customer and partner conversations (CXO and enterprise‑architect audiences).

Must‑Have Qualifications

• 12+ years building and shipping backend/data platforms, with demonstrated principal‑level ownership of at least one platform used by multiple product teams or external customers.
• Deep, hands‑on experience with at least two of: graph databases (Neptune, Neo4j), vector search (OpenSearch/Elasticsearch k‑N N, pgvector, Pinecone, Milvus), large‑scale key‑value/document stores (DynamoDB, Cassandra), and event streaming (Kafka/Kinesis).
• Strong distributed‑systems fundamentals: consistency models, partitioning, caching strategies, backpressure, and designing for p99 latency targets.
• Working knowledge of LLM application architecture: RAG, embeddings, context‑window management, agent frameworks, and evaluation of retrieval quality.
• Production AWS depth — the Aivar platform is AWS‑native (Bedrock, EKS/Lambda, Neptune/OpenSearch, DynamoDB, S3, KMS, PrivateLink).
• Proven security and compliance literacy for enterprise data platforms: encryption at rest/in transit, tenancy isolation, audit logging, and data‑retention policy enforcement.
• Excellent written communication — design docs, ADRs, and customer‑facing architecture narratives.

Nice‑to‑Have

• Prior work on memory systems for AI agents, personalization platforms, customer data platforms (CDPs), identity/entity resolution, or feature stores.
• Experience with knowledge‑graph construction from unstructured data (NER, relation extraction, entity linking).
• Exposure to Anthropic/Claude, Bedrock agent tooling, or the Model Context Protocol (MCP).
• Experience deploying into sovereign, on‑prem, or regulated environments (RBI/IRDAI/HIPAA‑adjacent).
• Early‑stage or zero‑to‑one product experience; comfort with ambiguity and rapid iteration.

What Success Looks Like (First 12 Months)

• Aiva v1 architecture is documented, reviewed, and in production behind at least two accelerators (Convogent and Velogent) at one or more enterprisecustomers.
• Hybrid retrieval meets agreed latency SLOs for voice workloads, with recall‑quality benchmarks tracked release over release.
• Multi‑tenant isolation and governance controls pass enterprise security review at a regulated customer.
• A 3–5 person Aiva team is hired, productive, and operating with a clear technical roadmap.