Software Engineer – AI & Autonomous Agents

Company: Autonoms AI • Location: Remote — Austin, TX, US • Employment: Contract

About the role

We are looking for a Software Engineer with strong experience building AI-powered applications and autonomous agents. This role combines traditional software engineering with modern AI development. You will be responsible for taking business requirements or product ideas, designing technical solutions, building applications, integrating APIs and AI models, and deploying working products. You will also build AI agents capable of reasoning, using tools, interacting with APIs and external systems, maintaining context, and completing multi-step tasks with limited human intervention.

Responsibilities

• Software Development: Design, build, test, deploy, and maintain web applications and internal software tools.
• Develop frontend and backend applications using JavaScript, TypeScript, Python, React, Next.js, Node.js, FastAPI, or similar technologies.
• Build and consume REST APIs and webhooks.
• Integrate third-party APIs, SaaS platforms, databases, and internal systems.
• Implement authentication, authorization, and appropriate access controls.
• Work with databases such as PostgreSQL, Supabase, MongoDB, or similar technologies.
• Write clean, maintainable, and well-documented code.
• Review, debug, and improve existing codebases.
• Use Git and GitHub for source control and development collaboration.
• AI and Autonomous Agent Development: Build autonomous and semi-autonomous AI agents capable of completing multi-step tasks.
• Design agent workflows involving reasoning, planning, tool usage, memory, and external systems.
• Integrate LLMs including OpenAI, Claude, Gemini, and other AI models into applications.
• Implement LLM tool/function calling and structured outputs.
• Connect AI agents to external tools, databases, APIs, SaaS platforms, and internal systems.
• Build multi-agent systems where specialized agents collaborate to complete complex workflows.
• Implement agent memory, context management, retrieval systems, and state management.
• Work with Model Context Protocol (MCP) and similar approaches for connecting AI systems to external tools.
• Build AI-powered applications, internal business tools, SaaS products, and automated workflows.
• AI-Assisted Development: Use modern AI development tools such as Claude, Claude Code, Base44, Lovable, Cursor, Replit, and similar platforms to accelerate development.
• Use AI-assisted coding tools to prototype, build, debug, test, and iterate on applications.
• Evaluate new AI models, development platforms, frameworks, and tools for practical use in software development.
• Maintain engineering quality while using AI-assisted development workflows.
• AI Reliability and Engineering: Implement error handling, retries, fallbacks, validation, and recovery mechanisms for AI workflows.
• Build human-in-the-loop approval processes where required.
• Implement appropriate agent permissions and controls.
• Develop logging, monitoring, and observability for AI systems.
• Test and evaluate AI systems to ensure they consistently perform their intended tasks.
• Debug AI workflows when agents produce unexpected results or fail to complete tasks.
• Implement API security, secret management, rate limiting, and other production controls.
• Manage AI usage and infrastructure costs.