Synagi
At Synagi, we are pushing the frontier of distributed and decentralised AI agents. Our research spans vector-driven retrieval systems, agentic swarms, and resource-efficient multi-agent architectures—all with a sharp focus on real-world performance and human-in-the-loop alignment. We explore scalable, context-aware multi-agent designs that outperform monolithic approaches and keep compute costs in check.
Role
As our Lead Backend & Cloud Engineer you will architect and own the entire high-throughput backend that powers Synagi's agent swarms. You'll write production-grade
Python
services that sustain tens-of-thousands of concurrent HTTP requests, expose clean gRPC/WebSocket/REST APIs, and keep everything shipping through automated CI/CD on Kubernetes. Your work is the foundation on which future research agents, and ultimately Synagi's vision of synergetic general intelligence will run. Core Responsibilities
Design, build, and operate
low-latency, scalable backend services
in Python (e.g., FastAPI, aiohttp) that crawl the web, orchestrate agents, and stream data at high QPS. Implement
gRPC, WebSocket, and REST
endpoints for internal and public consumption. Own
containerisation (Docker) and Kubernetes
deployments, including GitHub Actions–driven CI/CD pipelines and Helm/Terraform automation. Instrument everything with
Prometheus
metrics for performance and uptime monitoring. Collaborate with the AI Platform Engineer to integrate vector databases such as
Pinecone
into production search workflows. Must-Have Qualifications
3+ years
building high-QPS backend services in
Python , with deep knowledge of async runtimes. Proven production experience shipping
gRPC, WebSocket, and REST
APIs. Hands-on expertise with
Kubernetes, Docker, and GitHub Actions
(or similar CI/CD). Solid grasp of performance profiling, capacity planning, and incident response for distributed systems. Production experience with
Pinecone
vector database for semantic search and embedding workflows. Nice-to-Haves
Experience building
AI agents . Familiarity with
vector stores
such as Vespa or Milvus for large-scale similarity search. Interest in
WebAssembly / edge compute
to push ultra-low-latency functions closer to users. Applying
Send your resume—plus a short note (3–5 sentences) describing a production system you scaled or a performance bug you crushed—to garv.s.rawlot@gmail.com . We offer highly competitive salary, early-stage equity, and an opportunity to be the backbone of the future of Synergetic General Intelligence . Synagi is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
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As our Lead Backend & Cloud Engineer you will architect and own the entire high-throughput backend that powers Synagi's agent swarms. You'll write production-grade
Python
services that sustain tens-of-thousands of concurrent HTTP requests, expose clean gRPC/WebSocket/REST APIs, and keep everything shipping through automated CI/CD on Kubernetes. Your work is the foundation on which future research agents, and ultimately Synagi's vision of synergetic general intelligence will run. Core Responsibilities
Design, build, and operate
low-latency, scalable backend services
in Python (e.g., FastAPI, aiohttp) that crawl the web, orchestrate agents, and stream data at high QPS. Implement
gRPC, WebSocket, and REST
endpoints for internal and public consumption. Own
containerisation (Docker) and Kubernetes
deployments, including GitHub Actions–driven CI/CD pipelines and Helm/Terraform automation. Instrument everything with
Prometheus
metrics for performance and uptime monitoring. Collaborate with the AI Platform Engineer to integrate vector databases such as
Pinecone
into production search workflows. Must-Have Qualifications
3+ years
building high-QPS backend services in
Python , with deep knowledge of async runtimes. Proven production experience shipping
gRPC, WebSocket, and REST
APIs. Hands-on expertise with
Kubernetes, Docker, and GitHub Actions
(or similar CI/CD). Solid grasp of performance profiling, capacity planning, and incident response for distributed systems. Production experience with
Pinecone
vector database for semantic search and embedding workflows. Nice-to-Haves
Experience building
AI agents . Familiarity with
vector stores
such as Vespa or Milvus for large-scale similarity search. Interest in
WebAssembly / edge compute
to push ultra-low-latency functions closer to users. Applying
Send your resume—plus a short note (3–5 sentences) describing a production system you scaled or a performance bug you crushed—to garv.s.rawlot@gmail.com . We offer highly competitive salary, early-stage equity, and an opportunity to be the backbone of the future of Synergetic General Intelligence . Synagi is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
#J-18808-Ljbffr