19 Sep
|
Seeker
|
Bengaluru
About Leaser AI
Leaser AI helps multifamily asset owners turn exposed inventory into signed
leases at the right economic cost.
Our platform connects market, inventory, demand, prospect, leasing, and revenue
signals. It uses that context to recommend and execute governed actions, measure
the resulting business outcomes, and make the next decision stronger.
We are building Decision Intelligence, not another dashboard, marketing
automation tool, or generic AI assistant.
The role
We are looking for a Platform Engineer who can strengthen the technical spine
beneath Leaser's products.
You will work across ingestion, identity and attribution, semantic metrics,
decision services, governed execution, and the infrastructure that makes those
capabilities reliable. This is a hands-on product engineering role with
meaningful architectural ownership.
You will be effective here if you enjoy moving between application code, data
systems, infrastructure, and production operations. This is not a narrowly
defined DevOps or SRE position.
What you'll work on
- Build reliable integrations with property-management systems, CRMs,
advertising platforms, analytics systems, and other operational data sources.
- Strengthen the identity and attribution spine connecting clicks, leads,
prospects, tours, applications, and signed leases.
- Develop canonical data models and metrics for exposure, occupancy, leasing
velocity, acquisition cost, effective revenue, and related outcomes.
- Build durable workflows for ingestion, backfills, OAuth refresh, write-backs,
retries, reconciliation, and failure recovery.
- Evolve the shared platform supporting Demand OS, Prospect OS, Revenue OS, and
the Command Center.
- Improve multi-tenant isolation, authorization, auditability, data lineage, and
observability.
- Build the governed action path from recommendation through approval,
execution, receipt, rollback, and outcome evaluation.
- Integrate AI models without allowing probabilistic behavior to redefine
business truth, permissions, or safety boundaries.
- Improve local development, testing, deployment, and production diagnostics
across independently deployable services.
- Make pragmatic architectural decisions appropriate for an ambitious early-
stage platform.
Our current stack
- TypeScript and Node.js
- NestJS services and APIs
- Next.js and React
- PostgreSQL and canonical SQL views
- dbt analytics models
- Docker and Docker Compose
- AWS, Terraform, ECR, and related cloud infrastructure
- Redis and Temporal-oriented workflow infrastructure
- Anthropic models for analysis, explanation, and assisted workflows
- A shared architecture spanning ingestion, attribution, metrics,
recommendations, actions, and AI-assisted operating surfaces
The repository currently behaves as a modular monolith over shared data,
deployed as distinct services. We value engineers who can preserve coherent
boundaries without introducing distributed-systems complexity before it is
justified.
What we're looking for
- Strong production experience with TypeScript, Node.js, and backend application
development.
- Fluency with PostgreSQL, relational modeling, SQL, migrations, and data
integrity.
- Experience designing and operating APIs, asynchronous jobs, integrations, or
event-driven workflows.
- Practical knowledge of AWS, containers, infrastructure as code, deployment
automation, and production observability.
- A strong instinct for idempotency, retries, reconciliation, audit trails, and
failure handling.
- The ability to work across service, data, and infrastructure boundaries
without losing sight of the user outcome.
- Clear technical judgment about what should be centralized, what should remain
modular, and what should not be built yet.
- Comfort working in an evolving codebase where you will improve foundations
while continuing to ship product.
Especially valuable
- Experience with dbt, BigQuery, Snowflake,
or semantic metrics layers.
- Experience with Temporal, Dagster, or another durable workflow system.
- Work involving OAuth integrations, credential management, rate limits, schema
drift, or large backfills.
- Experience building multi-tenant enterprise software with row-level
permissions and audit requirements.
- Familiarity with identity resolution, attribution, experimentation, or causal
measurement.
- Experience building guarded AI or agentic systems that can recommend and
execute real-world actions.
- Knowledge of multifamily, property technology, advertising technology, or
revenue-management systems.
How we think about engineering
- Business definitions should be computed once and consumed everywhere.
- Every external action should be authorized, idempotent, observable, and
auditable.
- Missing or stale data must be visible rather than silently converted into
certainty.
- AI can interpret ambiguity; it cannot invent permissions, metrics, or business
truth.
- The best architecture is the simplest one that preserves trust and supports
the next stage of growth.
- Production outcomes matter more than architectural theater.
What success looks like
Within your first several months, you will have:
- Shipped meaningful improvements across the shared platform.
- Made one or more critical ingestion or execution workflows materially more
reliable.
- Improved the consistency and traceability of data from source signal to
signed-lease outcome.
- Reduced the effort required to diagnose failures and operate the platform.
- Helped establish engineering patterns that future product surfaces can reuse
safely.
- Developed enough product context to challenge requirements and recommend
simpler, stronger approaches.
Why join
You will help build the foundations of a recent kind of enterprise system: one that
does not merely automate work, but connects decisions to measurable outcomes and
learns from what happens next.
The problems are technically demanding, commercially meaningful, and still open
enough for one strong engineer to shape how the platform develops.
📌 Platform Engineer (Bengaluru)
🏢 Seeker
📍 Bengaluru