Founding AI Engineer

REM is building an autonomous software delivery platform that runs software delivery end to end with enterprise-grade reliability, control, and governance.

As AI systems begin participating directly in engineering workflows, the hard problem is no longer generation. It is making autonomous systems execute reliably across complex enterprise environments while maintaining control, observability, traceability, and safe behavior.

We are building the AI systems layer that makes this possible.

We are hiring a Founding AI Engineer to help design and build the core AI systems powering REM.

This is a deeply technical founding role focused on agent runtimes, context systems, model interaction, evaluation infrastructure, and runtime reliability for autonomous engineering workflows.

You will work directly with the founder and early engineering team to define how autonomous AI systems behave safely, reliably, and deterministically inside enterprise engineering environments.

This is not a prompt engineering or experimentation-only role.

We are looking for engineers who have built production AI systems and understand how models, context, tools, and runtime behavior interact in real-world applications.

Design and build runtime systems that enable AI agents to execute complex engineering workflows safely across tools, APIs, and enterprise systems.

Build context infrastructure for retrieval, memory persistence, knowledge grounding, and long-running execution workflows.

Design abstractions for model interaction, inference management, structured outputs, streaming execution, fallback handling, and intelligent model routing.

Build evaluation systems for agent behavior, execution correctness, retrieval quality, regression detection, and continuous reliability improvement.

Design policy enforcement, execution boundaries, validation layers, observability, and operational safeguards for autonomous systems.

Help shape architecture, engineering abstractions, and long-term technical direction for REM's AI systems platform.

Typically 5–10 years of engineering experience across backend systems, AI systems, platform engineering, or related domains, with meaningful hands-on experience building production AI / LLM systems.

Strong candidates typically have experience in several of the following:

• agent runtimes or multi-agent systems
• production LLM / GenAI systems
• retrieval / RAG / context engineering
• model routing or inference abstractions
• AI evaluation / observability / feedback systems
• strong backend engineering in Python and production APIs
• solid distributed systems fundamentals

Experience with developer tooling, workflow systems, execution frameworks, or enterprise AI platforms is a strong plus.

You should be comfortable operating in ambiguous early-stage environments and thinking in systems rather than isolated features.

In the first few months, success means:

• shaping REM's core AI systems architecture
• improving how autonomous systems retrieve, maintain, and use context
• building reliable agent runtime and model interaction infrastructure
• influencing critical technical decisions across the platform
• collaborating closely with the founding engineering team
• participating in technical architecture discussions with customers where needed

Over time, this role is expected to evolve into a major technical leadership position.

We value:

• first-principles thinking
• strong engineering judgment
• high agency
• low ego collaboration
• intellectual honesty
• building durable systems over short-term hacks

This is a founding-stage environment. Problems are ambiguous, constraints evolve quickly, and many patterns do not yet exist.

Bangalore

• competitive cash compensation
• meaningful founding-stage equity
• significant technical ownership and long-term influence