Fluid AI Python AI Engineer – Autonomous Agents: Remote Job in India
Fluid AI is hiring a Python AI Engineer – Autonomous Agents to help build and improve its enterprise Agentic AI Platform. The full-time role is listed as remote in India and is open to candidates with 0–5 years of software development experience, including fresh graduates.
What distinguishes this position is its focus on the engineering infrastructure behind autonomous AI agents. Rather than building only individual chatbots or applications that call language models, engineers will work on agent orchestration, reusable workflow components, integrations, and platform architecture.
Job Details
| Detail | Information |
|---|---|
| Company | Fluid AI |
| Job title | Python AI Engineer – Autonomous Agents |
| Job type | Full-time |
| Location | Remote, India |
| Experience | 0–5 years |
| Primary language | Python |
| Core focus | Autonomous agents and AI platform engineering |
| Salary | Not disclosed in the official listing |
| Application deadline | Not specified |
What You’ll Work On
The role centres on building the underlying platform that enables AI agents to coordinate tasks, interact with external systems, and support complex enterprise workflows.
Responsibilities include:
- Developing new features and capabilities for the Fluid AI Agentic Platform.
- Designing autonomous agent architectures and orchestration mechanisms.
- Building reusable Python components for AI workflows, memory, tools, and integrations.
- Improving platform scalability, performance, reliability, and developer experience.
- Connecting the platform to enterprise systems, APIs, databases, and external services.
- Working with large language models (LLMs), retrieval-augmented generation (RAG) pipelines, vector databases, and AI infrastructure.
- Contributing to architectural decisions and the platform’s technical direction.
The engineering challenge is not simply making an AI model generate a response. It is helping build the systems that coordinate agent behaviour, connect agents to tools and data, and support more complex workflows.
Required Skills
Fluid AI identifies these as the core requirements:
- Strong Python programming skills.
- Understanding of data structures, algorithms, and software engineering fundamentals.
- Familiarity with REST APIs and backend development.
- Strong debugging and problem-solving ability.
- Between 0 and 5 years of software development experience.
- Curiosity and willingness to learn about emerging AI systems.
The company explicitly welcomes fresh graduates, so the listing does not restrict applications to candidates with several years of professional experience.
Good-to-Have Skills
The following technologies and experiences can strengthen an application but are listed as desirable rather than mandatory:
- Python frameworks: FastAPI and AsyncIO.
- Infrastructure: Docker, Kubernetes, Linux, and cloud platforms.
- AI agent frameworks: LangGraph, LangChain, CrewAI, or similar tools.
- AI integration: Experience with LLMs and the Model Context Protocol (MCP).
- Systems engineering: Distributed systems and workflow orchestration.
- Practical projects: Open-source contributions or personal AI projects.
Candidates do not need to interpret every item in this list as a compulsory qualification. The stated core requirements focus on Python, programming fundamentals, backend/API familiarity, and problem-solving.
Who Should Apply?
This opportunity may suit computer science graduates, Python developers, backend engineers, and early-career software developers interested in moving into AI platform engineering.
A relevant personal project could demonstrate how well you understand the work. For example, a Python application that coordinates multiple tools through an API, maintains workflow state, and handles failures would be more directly relevant than a basic chatbot that only sends prompts to an LLM.
That is a suggested project direction based on the role’s technical focus, not a requirement stated by Fluid AI.
Why Consider Fluid AI?
The role offers the opportunity to work on platform-level engineering problems involving agent orchestration, distributed workflows, enterprise integrations, and scalable AI infrastructure.
Fluid AI describes its platform as serving organisations across sectors such as banking, financial services, manufacturing, and the public sector. For engineers interested in how AI systems move beyond demonstrations into enterprise workflows, this role offers a relevant area of technical work.
How to Apply
The position is listed on Fluid AI’s official careers website.