AI Engineer

Weekday AI (YC W21); Hyderabad; On-site; INR 300,000 - 2,200,000; Full time

Job summary

Weekday AI in Hyderabad is seeking an experienced AI Engineer to design and develop AI/ML and Generative AI POCs across business applications. The role focuses on translating problems into working AI-driven solutions and evaluating feasibility and scalability.

The ideal candidate has hands-on experience in ML, NLP, Generative AI, LLMs, Python, embeddings, and RAG architectures. You will work with business and technical stakeholders to prototype rapidly and deliver production-ready APIs and data

Qualifications

• 4+ years of experience in AI Engineering, ML, Data Science, or NLP.
• Strong hands-on expertise in ML, NLP, and Generative AI.
• Proven experience building AI/ML prototypes and rapid PoCs.
• Experience with Large Language Models such as GPT, Llama, Mistral, Claude.
• Proficiency with LangChain, LlamaIndex, Semantic Kernel, or similar frameworks.
• Strong Python programming skills and API development experience.
• Solid understanding of embeddings, vector databases, semantic search, and RAG architectures.
• Experience with Azure, AWS, or GCP; Azure OpenAI is a plus.
• Knowledge of model evaluation, fine-tuning, retrieval optimization, and experiments.
• Exposure to agentic AI, transformers, multimodal AI, and emerging Generative AI architectures.

Responsibilities

• Design and develop AI/ML and Generative AI PoCs to validate new business use cases.
• Translate business problems into scalable AI-driven solutions.
• Build LLM-powered applications using models like GPT, Llama, Mistral, Claude.
• Develop AI apps using LangChain, LlamaIndex, and Semantic Kernel.
• Rapidly evaluate feasibility across ML, NLP, Generative AI, and LLM use cases.
• Design and implement RAG architectures using embeddings, vectors, and pipelines.
• Develop APIs, microservices, data pipelines, and integrations to operationalise AI.
• Experiment with model fine-tuning, embeddings, vector search, prompts optimization, and evaluation.
• Prototype emerging AI capabilities like transformers, agentic workflows, multimodal models, and RAG techniques.
• Leverage Azure, AWS, and GCP cloud services; Azure OpenAI experience is advantageous.
• Apply lightweight MLOps covering model/versioning, monitoring, and evaluation.
• Analyse POC results and present findings to leadership.
• Collaborate with data scientists, engineers, product teams, and stakeholders.
• Stay current with Generative AI, LLMs, AI agents, NLP, and ML technologies.

Skills

Python

NLP

Generative AI

LLMs

RAG architectures

Embeddings

Vector databases

LangChain

LlamaIndex

Semantic Kernel

APIs

MLOps

Cloud platforms

Tools

LangChain

LlamaIndex

Semantic Kernel

Job description

Job Description:

This role is for one of the Weekdays clients

Salary range: Rs 300000 - Rs 2200000 (ie INR 3-22 LPA)

Experience: 4+ yrs

Location: Hyderabad

Job Type: Full-time

We are looking for an experiencedAI Engineerto design and develop innovativeAI/ML and Generative AI Proofs of Concept (POCs)across a range of business applications. The role focuses on rapidly translating business problems into working AI-driven solutions and evaluating the feasibility, effectiveness, and scalability of emerging AI technologies.

The ideal candidate will have strong hands-on experience inMachine Learning, NLP, Generative AI, Large Language Models (LLMs), Python, RAG architectures, embeddings, and vector databases. You should be comfortable experimenting with new technologies, building prototypes quickly, and collaborating with business and technical stakeholders.

Key Responsibilities

• Design and developAI/ML and Generative AI Proofs of Concept (POCs)to validate new business use cases.
• Translate business problem statements into practical and scalable AI-driven solutions.
• BuildLLM-powered applicationsusing models such as GPT, Llama, Mistral, Claude, and other foundation models.
• Develop AI applications using frameworks such asLangChain, LlamaIndex, and Semantic Kernel.
• Rapidly evaluate technical feasibility acrossMachine Learning, NLP, Generative AI, and LLMuse cases.
• Design and implementRAG architecturesusing embeddings, vector databases, retrieval pipelines, and prompt engineering techniques.
• Develop APIs, microservices, data pipelines, and integrations required to operationalise AI solutions.
• Conduct experiments involvingmodel fine-tuning, embeddings, vector search, prompt optimisation, and model evaluation.
• Explore and prototype emerging AI capabilities, includingtransformers, agentic workflows, multimodal models, and advanced RAG techniques.
• Leverage cloud AI services acrossAzure, AWS, and GCP, with exposure to Azure OpenAI being an advantage.
• Apply lightweight MLOps practices covering model and code versioning, evaluation, monitoring, and experimentation.
• Analyse POC results and assess solution performance, feasibility, scalability, and potential business value.
• Present POC outcomes, technical findings, insights, and recommendations to business and senior leadership.
• Collaborate with data scientists, software engineers, product teams, and business stakeholders throughout the development lifecycle.
• Stay current with the latest developments inGenerative AI, LLMs, AI agents, NLP, and machine learning technologies.

What Makes You a Great Fit

• 4+ years of experiencein AI Engineering, Machine Learning, Data Science, NLP, or a closely related field.
• Strong hands-on expertise inMachine Learning, NLP, and Generative AI.
• Proven experience buildingAI/ML prototypes and rapid Proofs of Concept.
• Strong practical experience working withLarge Language Models (LLMs)such as GPT, Llama, Mistral, Claude, or equivalent models.
• Proficiency withLangChain, LlamaIndex, Semantic Kernel, or similar LLM application frameworks.
• Strong programming skills inPythonand experience developing APIs and AI-enabled services.
• Solid understanding ofembeddings, vector databases, semantic search, prompt engineering, and RAG architectures.
• Experience with cloud platforms such asAzure, AWS, or GCP; Azure OpenAI experience is preferred.
• Understanding of LLM evaluation, fine-tuning, retrieval optimisation, and model experimentation.
• Exposure toagentic AI, transformers, multimodal AI, and emerging Generative AI architectures.
• Familiarity with API development, microservices, data pipelines, and software engineering practices.
• Understanding of lightweightMLOps, model versioning, monitoring, and evaluation.
• Strong analytical and problem-solving abilities with a practical, experimentation-driven mindset.
• Excellent communication skills and the ability to explain complex AI concepts to technical and non-technical stakeholders.
• Ability to work effectively inAgile, collaborative, and fast-paced environments.
• Curiosity and enthusiasm for experimenting with emerging AI technologies and turning new ideas into working solutions.

Requirements: