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Agent Infrastructure Engineer — Core Harness (Superagent)

ImagineArtIndiaEngineering
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Salary
Not listed
Job type
Full-time
Work mode
Remote
Posted
18 Aug 2026
Status
Open · checked 7d ago

About this role

Role Overview

ImagineArt is hiring a remote Agent Infrastructure Engineer to lead the architecture and evolution of Superagent, the core agent harness powering multi-step workflows. This full-time position requires at least four years of software engineering experience and suits developers passionate about building robust, production-scale artificial intelligence systems.

Key Responsibilities

Own the architecture, development, and evolution of Superagent, the core agent harness powering conversations, tool calls, and multi-step agentic workflows.
Design and optimize the agent execution loop focusing on latency, reliability, token efficiency, cost, and task completion.
Build and improve core harness systems including context management, memory and state handling, tool routing, function schemas, structured outputs, retries, and error recovery.
Construct and maintain agent evaluation infrastructure to measure quality and drive data-informed engineering choices.
Integrate and benchmark multiple large language model providers and models, assessing performance, cost, reliability, and capabilities.
Implement performance optimizations such as caching, batching, parallel tool execution, and prompt or context compression.
Create deep observability and instrumentation across agent runs, covering tracing, logging, metrics, and regression detection.
Extend and customize underlying agent frameworks when existing abstractions fail to meet technical demands.
Build reliable integrations with evolving artificial intelligence and tool ecosystems.
Collaborate closely with product engineering teams to provide clean abstractions while hiding harness complexity.
Troubleshoot and resolve complex problems across non-deterministic, distributed, and model-driven systems.

Requirements

Minimum of 4 years of professional experience in software engineering, backend engineering, or systems infrastructure.
Strong proficiency in Python and/or TypeScript.
Hands-on background in building or operating large language model based agents in production environments.
Solid understanding of tool calling, function schemas, context limits, structured outputs, model failures, and unreliable artificial intelligence behavior.
Experience utilizing at least one agent framework like LangGraph, OpenAI Agents SDK, CrewAI, AutoGen, or a custom agent harness.
Clear comprehension of agent orchestration and multi-step workflows.
Experience creating or working with evaluation suites, benchmarks, A/B testing, or measurement systems for artificial intelligence products.
Strong grasp of concurrency, caching, profiling, performance optimization, and latency or cost tradeoffs.
Experience interacting with large language model APIs and production artificial intelligence infrastructure.
Excellent debugging and problem-solving abilities tailored to complex and non-deterministic systems.
Proactive, self-driven builder mindset with a strong passion for technology.

Nice to Have

Contributions to open-source agent frameworks, artificial intelligence tooling, or infrastructure.
Experience with Retrieval-Augmented Generation pipelines, vector databases, or long-term memory systems for artificial intelligence agents.
Familiarity with the Model Context Protocol or similar tool-integration standards.
Experience handling large language model inference infrastructure, model routing, rate limits, fallbacks, or high-volume model APIs.
Experience working with LangChain, LlamaIndex, LangGraph, DSPy, or similar artificial intelligence infrastructure frameworks.
Experience with Kubernetes, Docker, cloud infrastructure, or distributed systems.
Background in building internal developer platforms or infrastructure utilized by multiple engineering and product teams.
Strong familiarity with observability, distributed tracing, and production reliability.
Contributions to open-source projects or personal artificial intelligence infrastructure initiatives.

Skills and Tools

Python
TypeScript
Kubernetes
Docker
Large Language Models (LLMs)
LangChain
Retrieval-Augmented Generation (RAG)

About the Company

ImagineArt is a rapidly growing generative artificial intelligence company operating without outside funding. The organization has crossed 35 million dollars in annual recurring revenue, generated over 100 million social impressions, and built an image generation model ranked third globally for photo realism.

How to Apply

Apply directly on the official company careers page to submit your application for this remote position.

Skills and tech stack

Questions candidates ask

What experience is required for this role?

Candidates must have at least 4 years of experience in software engineering, backend engineering, or systems infrastructure, along with hands-on experience building or operating large language model agents in production.

Is this position remote?

Yes, this role is fully remote.

What programming languages are required?

Strong proficiency in Python and/or TypeScript is required.

What will I be working on primarily?

You will own Superagent, ImagineArt's core agent harness, focusing on orchestration loops, tool-calling infrastructure, memory management, streaming, retries, evaluation, and observability.

Are there optional skills that can help my application?

Yes, helpful optional skills include experience with Kubernetes, Docker, RAG pipelines, vector databases, Model Context Protocol, open-source contributions, and frameworks like LangChain, LlamaIndex, or LangGraph.

Ready to apply?

The application is on the official ImagineArt careers page.

Apply on company site