Principal AI/LLM Engineer - Agentic Orchestration - Immediate joiners preferred - 75 LPA++

Hiring for: A US based well funded startup building low-latency, agentic voice AI systems at production scale.

Role: Principal AI / LLM Engineer Agentic Orchestration

Experience: 8yrs+

Location: Bengaluru

Type: Hybrid - 3 days Work From Office

Notice: Immediate preferred, no longer than 30 days

Salary: Based on fitment (75L range + massive ESOPs)

Role:

- Design and own the orchestration layer (control plane) powering production AI agent systems building multi-step workflows that coordinate models, tools, and services with deterministic execution and controlled failure.

- This role sits at the intersection of AI systems and workflow orchestration, where LLM-driven agents interact with APIs, data systems, and internal services through structured execution pipelines.

Here's what you're EXTREMELY good at:

- Shipping production AI agent systems (not prototypes or experiments) that orchestrate models, tools, and services

- Designing multi-step agent workflows with deterministic execution and clear state transitions

- Building orchestration layers that coordinate LLM reasoning, tool execution, and system state using patterns such as state machines, schedulers, or operator-style reconciliation loops

- Modeling state machines, dependency chains, and workflow DAGs

- Designing guardrails, invariants, and safety boundaries for AI agent behavior

- Handling retries, idempotency, compensating actions, and partial failures in complex workflows

- Building systems that remain reliable when agents interact with external tools and APIs

- Owning systems end-to-end: design production rollout incident recovery

- Working with event-driven architectures, workflow engines, distributed schedulers, or orchestration platforms (e.g. Temporal, Cadence, LangGraph, LangChain, LlamaIndex, Airflow, Step Functions, Argo or similar)

Here's how your peers and manager describe you:

- Thinks in states, transitions, and constraints, not just function calls

- Instinctively asks How does this break? before discussing how it works

- Decomposes complex AI systems into clear orchestration layers and execution components

- Designs abstractions that remain stable under scale, concurrency, and partial failure

- Understands that agent behavior must be deterministic and observable in production

- Moves fast without sacrificing structural integrity

- Adapts your model when challenged instead of defending weak assumptions

This is NOT who you are:

- Someone experimenting with LLM APIs without having shipped production AI systems

- A prompt engineer focused only on model tuning or chaining APIs

- A research-only AI/ML profile without production system ownership

- A generic backend engineer whose work stops at CRUD microservices

- A people manager stepping away from hands-on system design