Memory Systems Engineer

3 days ago


Odisha, India Particle Execution Full time ₹ 15,00,000 - ₹ 20,00,000 per year

About Particle Execution:

We're an AI solutions specialist and we're building modular AI infrastructure for execution - including a

second brain for our clients.

Second brain is a scalable knowledge and content-generation system that supports high-context AI agents for all our clients. It stores, learns from, and reasons with everything your business knows - enabling execution through strategy, content, and conversation.

We're now looking for an engineer who can work with the rest of our team and can help us turn per-client data into a persistent, intelligent memory system.

The Role:

We're hiring a Memory Systems Engineer to design and build the backbone of our product's long-term memory - initially for content automation, eventually for agentic workflows across industries. This is a hands-on role for someone who can ship fast, but also think deeply about system design. You'll work closely with the team to architect, test, and evolve how memory works across vector search, feedback integration, and contextual retrieval.

What You'll Build:

A modular, per-client

memory system

that supports:

Dense vector retrieval

(FAISS, Qdrant, Weaviate)

Feedback-aware updates

based on edits, ratings, and post performance

Dynamic context routing

based on generation type (e.g. strategy vs post)

A scalable infrastructure to support:

Dozens → thousands of clients

Low-latency retrieval and context injection for LLM generation

(Optional but welcome) Foundations for:

Graph-based or symbolic memory layers

Tree-of-thought traceability

Agent memory logs and replayable reasoning chains

You Might Be a Fit If You:

Have built or contributed to

LLM-integrated apps or systems Know how to build

RAG pipelines

from scratch (chunking, embedding, querying) Have worked with

vector databases

(FAISS, Qdrant, Pinecone, etc.) Have strong opinions on

how memory should evolve over time Care about building

real-time, adaptive, and traceable

AI systems Think pragmatically now, but architect for future generalization

Bonus Points For:

Experience with LangChain, LlamaIndex, or LangGraph Familiarity with graph databases (Neo4j, Dgraph) or key-value memory systems (Redis, DuckDB) Knowledge of hyperdimensional memory or symbolic-connectionist hybrids A portfolio or writeup of RAG or memory system design

What You'll Get:

Ownership over

core product infrastructure A chance to influence how

next-gen AI agents think and remember A team that moves fast, thinks big, and builds practically Competitive comp A growing customer base and a roadmap full of execution challenges

We're not just building AI that chats. We're building AI that remembers, improves, and executes. If you think memory is the key to agentic intelligence - we want to talk.



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