Sr. Solutions Architect
18 hours ago
Position: Sr. Solution Architect — Large Behavioural Model (LBM) Ecosystem
Location:
Bangalore (Onsite Only)
Type:
Part-time | Immediate Joiners Preferred
Experience:
7+
Contact:
About Assessli
Assessli
is building the world's first
Large Behavioural Model (LBM)
— a self-evolving AI framework that understands
how humans think, behave, and adapt.
Our mission is to create the foundation of
Human–AI Symbiosis
through a multi-agent behavioural intelligence platform and
Physical AI Companion
that bridges human cognition with machine reasoning.
We're looking for a
Solution Architect
who can design the backbone of this new AI ecosystem — someone who thrives at the intersection of large-scale data, distributed intelligence, and system architecture.
Role Overview
As the
Solution Architect
, you'll lead the design and architecture of Assessli's
LBM platform
— a distributed, data-driven, and multi-agent system that integrates real-time behavioural signals, AI agents, and decision orchestration pipelines.
You'll work closely with the
CTO and AI core team
to transform LBM's theoretical framework into a reliable, secure, and scalable production infrastructure.
Key Responsibilities
- Architect and document end-to-end system design across backend, API, data, and AI agent layers.
- Design data pipelines connecting
mobile, wearable, and backend systems
with the LBM inference engine. - Implement scalable frameworks for
knowledge graphs, embeddings, and behaviour-driven data models. - Define standards for
API design, caching, async workflows, and event-driven systems. - Build privacy-first data pipelines integrating
security, consent, and ethical AI principles. - Oversee CI/CD pipelines, observability, and production readiness for multi-agent orchestration.
- Review and mentor development teams to ensure performance, fault tolerance, and maintainability.
- Collaborate with neuroscience, AI, and product teams to translate LBM concepts into tangible systems.
Requirements
- 7+ years in
system architecture, backend engineering, or distributed AI platforms. - Deep expertise in
Python (FastAPI)
,
, or
Go
for backend microservices. - Hands-on experience with
PostgreSQL, Redis
, and
Graph/NoSQL databases (Neo4j, MongoDB, DynamoDB)
. - Proven experience designing
event-driven, microservice-based architectures
. - Proficiency in
AWS or GCP (ECS, Lambda, CloudWatch, Pub/Sub, etc.) - Familiarity with
vector databases, message queues (Kafka, RabbitMQ)
, and
knowledge graph systems. - Strong understanding of
data consent, privacy, and secure edge data design (GDPR, DPDPA)
. - Exceptional documentation, communication, and team leadership skills.
- Prior exposure to
AI, behavioural data, or R&D-focused systems
is highly preferred.
What You'll Deliver in the First 6 Months
A
scalable LBM architecture
connecting real-time behavioural data with AI agents.
A
robust backend system
ready for pilot deployment and multi-agent orchestration.
End-to-end
observability, security, and privacy frameworks
.
Mentorship for backend and AI teams to uphold
best practices in data-driven system design
.
Why Join Assessli
You won't just build another platform —
You'll
architect the intelligence layer of the next AI revolution.
At Assessli, engineers don't just write code; they build the future of how humans and AI coexist, learn, and evolve together.
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