Backend Developer
2 weeks ago
Overview
We're seeking a backend developer capable of designing, building, and optimizing
scalable, secure multi-agent systems
and
federated learning workflows
. You'll be working at the intersection of
AI automation
,
data privacy
, and
enterprise integrations
, powering intelligent systems that operate across distributed environments.
Key Responsibilities
- Design and develop
secure, high-performance multi-agent systems
with federated learning capabilities. - Build and maintain
workflow orchestration logic
using tools such as
n8n, LangGraph
, or
custom event pipelines
. - Develop and manage
endpoints for federated learning
and
encrypted edge-agent communication
. - Implement
authentication, authorization
, and
role-based access
using modern security frameworks. - Optimize
system performance, latency, and scalability
across large-scale enterprise datasets. - Implement
logging, monitoring
, and
error-handling mechanisms
for distributed agent workflows. - Collaborate closely with
frontend, AI, and DevOps teams
to ensure seamless integration and deployment.
Required Skills & Experience
- 3–6 years
of backend development experience. - Strong proficiency in
,
Python (FastAPI/Flask)
, or
TypeScript
. - Experience with
SQL databases
such as
PostgreSQL
,
MySQL
, or
Supabase
. - Solid understanding of
RESTful APIs
,
webhooks
, and
microservice design
. - Proven experience integrating with
external APIs
(e.g., Salesforce, Jira, Slack, etc.). - Strong grounding in
authentication, encryption
, and
security protocols
(JWT, OAuth2, E2E encryption). - Experience with
containerization (Docker)
and
cloud deployments
(Vercel, AWS, GCP, or Render). - Prior work with
AI-powered
or
data-driven systems
. - Hands-on experience with
federated learning
,
data privacy
, or
edge runtime logic
(required). - Familiarity with
LangChain, LangGraph
, or
n8n
for AI workflow orchestration. - Knowledge of
Supabase functions
,
Xano APIs
, or
Airtable automations
. - Understanding of
multi-agent architectures
and
reward-based self-improvement loops
.
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