Hiring for: A US based well funded startup building a temporal agentic operating system for long-running, stateful enterprise AI workflows at large global enterprises.
Role: Senior Backend & AI Orchestration Engineer
Positions: 1
Experience: 5 to 8 years
Location(s): Bengaluru
Type: On-site / Permanent
Salary: To be shared with shortlisted candidates
Notice Period: 30 days
Role:
You will build and own the orchestration and execution backbone powering AI-driven enterprise workflows at production scale.
This role sits at the intersection of:
- distributed systems
- workflow orchestration
- durable execution
- AI systems infrastructure
- real-time backend systems
- agent coordination
The systems you build will coordinate:
- AI agents
- humans
- enterprise systems
- asynchronous workflows
- retries and recovery
- long-running stateful processes
IMPORTANT:
- This is NOT a traditional CRUD backend role.
- The focus is on reliability, orchestration, execution guarantees, workflow continuity, and systems that continue operating correctly even under latency, retries, failures, and partial execution states.
What you'll bring
- Extremely strong backend engineering fundamentals using Python with Java or Go
- Clear ownership experience building and operating production-grade distributed backend systems
- Strong understanding of:
- concurrency
- async execution
- idempotency
- retries
- timeouts
- queues
- backpressure
- failure recovery
- state management
- Experience working with workflow orchestration systems or durable execution concepts such as:
- Temporal.io
- Cadence
- distributed job systems
- event-driven architectures
- workflow/state-machine engines
- Strong systems reasoning — you can explain:
- why systems fail
- how workflows degrade
- where bottlenecks emerge
- how recovery paths behave under load
- Experience building AI/ML-backed production systems, including:
- inference orchestration
- async model execution
- streaming pipelines
- multi-step AI workflows
- human-in-loop execution flows
- Comfort with real-time or streaming systems such as:
- WebSockets
- event streams
- low-latency systems
- WebRTC/voice systems (helpful but not mandatory)
- Strong bias toward observability, reliability, operational ownership, and production closure
- Ability to collaborate closely with AI/ML engineers building graph-driven and agentic intelligence layers
Experience with technologies/frameworks such as
- Python
- Go or Java
- Temporal.io / Cadence or similar durable workflow systems
- Agent frameworks (LangGraph, LangChain, AutoGen, CrewAI, etc.)
- Kafka or event-streaming architectures
- Redis, queues, async job systems
- gRPC, WebSockets, or real-time communication systems
- Distributed tracing and observability tooling
What this role is NOT
- A prompt engineering role
- A simple LLM integration role
- A REST API + microservices-only backend role
- A Kubernetes-only infrastructure role
- A telecom/SIP integration role
- A voice-only engineering role
- A frontend-heavy full stack role
- A research-only ML role
- A POC-to-demo engineering position
- A traditional enterprise Java CRUD development role
- A low-ownership implementation/support role
