# AI Engineer

> Weekday AI · Mumbai, India · Full-time · Posted 2026-09-10

**Salary:** INR 3,500,000–5,500,000

**Workplace:** on_site

**Department:** Weekday's Client via platform

## Description

**This role is for one of Weekday’s clients  
Salary range: Rs 3500000 - Rs 5500000 (ie INR 35 - 55 LPA)**

  
Min Experience: 7+ years  
Location: Mumbai, Maharashtra, India  
JobType: full-time

We are seeking a highly skilled and hands-on **AI Engineer** to design, build, and deploy production-grade Generative AI solutions for complex enterprise use cases. This role requires strong expertise in Artificial Intelligence, Machine Learning, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and modern AI application development.

The ideal candidate will have a strong engineering mindset and a proven ability to take AI solutions from concept to production. You will work closely with cross-functional teams, including product, engineering, data, and business stakeholders, to develop scalable, reliable, and high-performing AI applications that deliver measurable business outcomes.

## Requirements

Key Responsibilities

-   Design, develop, and lead end-to-end implementation of enterprise-grade Generative AI solutions.
-   Build scalable and production-ready AI applications for real-world business use cases.
-   Design and optimize **RAG pipelines**, including data ingestion, chunking, embeddings, retrieval, reranking, and grounded response generation.
-   Develop effective prompt engineering strategies to improve response quality, reliability, consistency, and task performance.
-   Work on model fine-tuning and adaptation techniques to improve model performance for domain-specific use cases.
-   Build and implement **Agentic AI workflows** involving tools, APIs, memory, reasoning, and multi-step execution.
-   Develop AI solutions using LLM orchestration frameworks for workflow management, tool calling, and multi-agent coordination.
-   Integrate Generative AI applications with enterprise platforms, internal applications, APIs, databases, and cloud services.
-   Evaluate and optimize AI models based on quality, accuracy, latency, hallucination risks, safety, scalability, and cost-performance trade-offs.
-   Develop reusable frameworks, standards, and best practices for designing, building, and deploying AI solutions at scale.
-   Collaborate closely with data, engineering, product, and business teams to identify use cases and rapidly move solutions from concept to deployment.
-   Implement AI application evaluation, monitoring, observability, and governance practices.
-   Ensure AI solutions follow enterprise security, responsible AI, and compliance requirements.
-   Contribute to LLMOps and MLOps practices, including model monitoring, deployment, versioning, and lifecycle management.

Required Skills and Qualifications

-   **7–10 years of experience** in AI/ML engineering, applied AI, intelligent application development, or related fields.
-   At least **3 years of hands-on experience in Generative AI**.
-   Proven experience designing and deploying at least one Generative AI solution into a production environment.
-   Strong understanding of AI and Machine Learning fundamentals.
-   Hands-on expertise with **Large Language Models (LLMs)** and modern AI application architectures.
-   Strong experience with **RAG, Prompt Engineering, embeddings, semantic search, and vector databases**.
-   Experience building Agentic AI applications and multi-step AI workflows.
-   Knowledge of model fine-tuning and adaptation techniques.
-   Strong programming skills in **Python**.
-   Experience with modern AI and LLM application frameworks and orchestration tools.
-   Experience with cloud-based AI services, preferably **AWS Generative AI services**.
-   Good understanding of LLM application design, evaluation, observability, deployment, and performance optimization.
-   Familiarity with APIs, enterprise system integrations, and cloud-based architectures.
-   Understanding of AI security, responsible AI practices, governance, and risk management.
-   Experience with **LLMOps/MLOps**, monitoring, and AI lifecycle management is preferred.

Must-Have Skills

-   Large Language Models (LLMs)
-   Artificial Intelligence (AI)
-   Retrieval-Augmented Generation (RAG)

Preferred Skills

-   Python
-   Prompt Engineering
-   Agentic AI
-   Vector Databases
-   Embeddings and Semantic Search
-   AWS Generative AI Services
-   LLMOps / MLOps
-   AI Orchestration Frameworks
-   Model Fine-Tuning

## Apply

[Apply at Weekday AI](https://apply.workable.com/weekday-1/j/5E36BE2754/apply)

---
Powered by [Workable](https://www.workable.com)