Founding Engineer

Founding Engineer — The Machine Brain (TMB)

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persistent identity

We’re hiring a founding engineer to focus on the representation, persistence, and lifecycle of machine identity — the part of the brain that answers “who is this agent?” across interactions, sessions, and embodiments.

As a Founding Engineer on TMB you’ll own how persistent identity and selfhood are engineered. You will design representations and systems that let agents remember who they are, revise beliefs coherently, maintain consistent values, and present a stable, accountable identity across channels and lifetimes.

• Design the

  Identity Substrate

  : durable, queryable representations for self (memory graphs, profile/state models, versioned self-models).
• Build identity lifecycle management: creation, evolution, reconciliation, merging, and archival of identity across sessions and modalities.
• Implement belief representation and revision mechanisms that support long-term coherence and Recursive Belief Revision-like flows.
• Anchor values, drives, and commitments to identity so agents act consistently and are auditable.
• Integrate persistent identity with LLM-based reasoning, multi-agent frameworks, and model orchestration to enable stateful decision-making.
• Define storage, retrieval, and consistency models (vector + symbolic hybrid retrieval, identity sharding, eventual/strong consistency tradeoffs).
• Build APIs, SDKs, and event contracts that expose identity, history, and provenance to agentic platforms.
• Design observability, testing, and safety controls for identity: explainability, privacy, reconciliation, and rollback.
• Productionize pipelines that convert experimental identity models into scalable, robust services.
• Collaborate closely with research to translate cognitive models into production systems and measurable guarantees.
  

• 3–4 years of hands-on experience building AI systems, LLM products, knowledge graphs, or stateful infrastructure.
• Strong background in Python and practical experience with embedding frameworks, vector DBs, and knowledge-graph tooling.
• Demonstrable experience designing data models for long-lived state, memory systems, or complex graph structures.
• Systems-minded: you can design for durability, latency, scale, and recoverability in distributed environments.
• Comfortable integrating symbolic and vector approaches to retrieval and reasoning.
• Product-oriented: pragmatic engineer who ships, measures, and iterates.
• Excellent communication skills: you can translate cognitive/academic concepts into engineering specifications.
• CS degree preferred; candidates from top institutes encouraged to apply. Strong project work (portfolio, GitHub, papers, demos) can substitute for formal credentials.
  

• Prior work on identity systems, user modeling, or persistent agent state.
• Experience with model serving and lifecycle infra, hybrid vector-symbolic retrieval, or multi-agent coordination.
• Familiarity with Rust/Go/C++ for performance-critical components.
• Background in privacy/security and accountable system design for long-lived state.
  

• Gurugram (strictly on-site)
• Full-time, founding engineering role with high ownership and impact
  

• ₹50,00,000 – ₹75,00,000 LPA (total package), negotiable up to ₹1,00,00,000 for exceptional candidates
• ESOPs / long-term incentives available for early team members
  

You’ll be a core architect of what “self” means for artificial agents — not just building reasoning components but creating the persistent identity that makes agents reliable, accountable, and human-compatible.

smartest-16@olbrain.com

• . Please include your current CTC.