Artificial Intelligence Engineer

This role involves designing and deploying AI agents and workflows for enterprise applications. You will work with LLMs, microservices, and distributed systems to build scalable, reliable AI solutions. The focus is on agent orchestration, tool integration, and production deployment.

• Pay is stated up front: $900. Most postings never say.
• Remote. The posting is listed for India; check it for any limit on where you can live or which time zone you work in.

Summarised by InternDoor from techolution’s posting, in our own words. The posting itself is the source of truth, so check it before you apply.

• Build scalable AI agents and workflows using LLMs, FastAPI, and distributed systems
• Integrate agents with external tools, APIs, and services using LangGraph or AutoGen
• Develop backend services for production AI applications on GCP or AWS

Required

• Experience 1–4 years of hands-on experience in Python development
• Backend Applications Strong experience building backend applications and APIs using FastAPI or Flask
• AI Agents Hands-on experience building or integrating AI Agents and Agentic AI workflows
• LLMs Strong understanding of LLMs, agent orchestration, multi-agent systems, tool/function calling, and agent workflows
• Frameworks Experience with LangGraph, AutoGen, CrewAI, or similar Agentic AI frameworks
• Microservices Strong understanding or hands-on experience with microservices, distributed systems, and event-driven architecture
• Distributed Tools Experience with technologies such as Celery, Kafka, RabbitMQ, Redis, or similar distributed processing tools
• Python Strong understanding of Python, OOP, asynchronous programming, and software engineering fundamentals
• Pydantic Experience with Pydantic, API development, data modeling, and NoSQL databases
• Git Good understanding of Git and version control

Nice to have

• RAG Experience with RAG, embeddings, and vector databases is preferred but Agentic AI experience is the primary focus
• MCP Experience with MCP (Model Context Protocol), Docker, Kubernetes, agent memory/state management, observability, and production-scale AI systems

Read from techolution’s posting. Its own wording is the one that counts.

1. Check what they ask for. Read the requirements above: techolution asks for 1–4 years.
2. Tailor your resume to the role. Put the work that matches these skills first. InternDoor’s resume tailor does it against this posting.
3. Apply on LinkedIn. The application is on linkedin.com, not on InternDoor. We never ask for a fee.

Apply soon: postings like this can close without notice, and this one states no deadline.

Posted

13 Nov 2026, on LinkedIn

First seen by InternDoor

13 Nov 2026, within 2 minutes of being posted

Last checked

13 Nov 2026: the posting was still in LinkedIn’s search results. We have not checked its application page.

Application deadline

techolution has not stated one

Leaves InternDoor

By 13 Dec 2026, our 30-day limit for LinkedIn listings, or sooner if the application closes

Application page

linkedin.com (Easy Apply)

What we checked, and what the dates mean

The date this listing leaves InternDoor is our own rule, not a deadline set by techolution. Postings can close earlier, at any time.

InternDoor has recorded 3 engineering postings from techolution in India since Nov 2026.

When this listing comes down, this address says the role has closed and lists open roles like it, instead of a dead end.

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