About this role
Full Time Senior Artificial Intelligence Engineer in AI at Weekday in India - Remote. Apply directly through the link below.
At a glance
- Work mode
- Remote
- Employment
- Full Time
- Location
- India - Remote
- Experience
- Senior · 4+ years
Core stack
- Artificial Intelligence
- Machine Learning
- Generative AI
- Observability
- Performance
- LangChain
- FastAPI
- Python
- Django
- Design
- Remote
- Azure
- SOLID
- LLMs
- SQL
- AWS
- GCP
- RAG
Quick answers
Is this Artificial Intelligence Engineer job remote?
Yes, this position is fully remote (India - Remote).
What skills are required?
Artificial Intelligence, Machine Learning, Generative AI, Observability, Performance, LangChain, FastAPI, Python, Django, Design, and more.
Weekday is hiring for this role. Visit career page
India - Remote, India
This role is for one of the Weekday's clients
Min Experience: 4 years
Location: Remote (India)
JobType: full-time
We are looking for hands-on Artificial Intelligence Engineers who can design, build, deploy, and own end-to-end AI systems. This role is ideal for practitioners who enjoy shipping production-ready GenAI solutions, working independently, and taking full ownership of AI-driven products.
Requirements
Key Responsibilities
- Design, build, and deploy LLM-powered applications, including RAG and agentic AI systems.
- Develop intelligent document processing and document understanding pipelines.
- Implement and optimize workflows using frameworks such as LangChain, LangGraph, and related orchestration tools.
- Build and deploy scalable AI services on cloud platforms including AWS, GCP, or Azure.
- Deliver production-grade AI solutions with a strong focus on performance, reliability, and speed of execution.
- Continuously evaluate and improve model outputs, prompts, and system architectures.
Required Skills & Qualifications
- Strong hands-on experience building Generative AI and LLM-based systems.
- Solid backend development experience using Python and frameworks such as FastAPI or Django.
- Practical experience with RAG architectures, embeddings, and vector databases.
- Working knowledge of machine learning fundamentals, MLOps practices, and model evaluation techniques.
- Ability to work independently, take ownership, and deliver outcomes end to end.
Preferred / Nice-to-Have
- Experience with tools such as LlamaCloud, LangSmith, or similar GenAI observability platforms.
- Exposure to prompt engineering, evaluation pipelines, and LLM monitoring.
- Experience integrating AI systems with structured data sources (SQL, APIs).
Core Skills
Artificial Intelligence · Generative AI · Large Language Models (LLMs) · RAG · Prompt Engineering · LangChain · LangGraph · LlamaCloud · LangSmith · Python · SQL · Machine Learning · MLOps