Generative AI Engineer

MOURI Tech; Hyderabad; On-site; INR 3,500,000 - 6,500,000; Full time

Job summary

MOURI Tech in Hyderabad is seeking an experienced AI / GenAI Engineer with 5-12 years in designing, developing, and deploying enterprise-grade AI and ML solutions. The role requires expertise in AI, ML, GenAI, LLMs, Agentic AI, RAG, Python, and Azure Databricks, and involves taking AI solutions from ideation to production, optimization, and monitoring.

You will design scalable enterprise AI solutions, build agents and chatbots, implement RAG pipelines, and work with cloud technologies to deliver

Qualifications

• 5–12 years hands-on experience in designing, developing, and deploying enterprise-grade AI/ML solutions.
• Strong expertise in Generative AI, LLMs, agentic AI, and RAG.
• Proficient in Python and cloud-based AI deployments on Azure.

Responsibilities

• Lead architecture and development of enterprise AI and GenAI solutions.
• Design, develop, train, evaluate, and deploy ML models for production.
• Implement prompt engineering, data processing, and model observability.
• Build AI-powered chatbots and conversational interfaces.
• Collaborate with data scientists, software engineers, and business stakeholders.
• Ensure solutions are scalable, secure, and cost-efficient.

Skills

AI

GenAI

Agentic AI

RAG

LLMs

Python

Azure Databricks

Education

Bachelor's or Master's in Computer Science / AI / Data Science / Engineering

Tools

Azure Databricks

REST APIs

Job description

We are looking for an experienced AI / GenAI Engineer with 5-12 years of hands-on experience in designing, developing, and deploying enterprise-grade AI and machine learning solutions.

The ideal candidate will have strong expertise in AI, Machine Learning, Generative AI, LLMs, Agentic AI, Chatbots, RAG, Python, and Azure Databricks. The candidate should be capable of taking AI solutions from ideation and experimentation through production deployment, optimization, and ongoing monitoring.

The role requires a strong combination of AI engineering, software development, data engineering, LLM application development, and cloud technologies, with the ability to work on scalable enterprise AI solutions.

Primary Skills

• Artificial Intelligence (AI)
• Generative AI (GenAI)
• Agentic AI / AI Agents
• Retrieval-Augmented Generation (RAG)
• AI-powered Chatbots
• Python

Key Responsibilities

• Design, develop, train, evaluate, and deploy machine learning models.
• Apply appropriate ML algorithms to solve complex business problems.
• Perform data preparation, feature engineering, model development, validation, and optimization.
• Build scalable AI/ML solutions for enterprise use cases.
• Evaluate model performance and continuously improve accuracy, scalability, and reliability.

Generative AI & LLM

• Design and implement Generative AI applications using LLMs.
• Work with commercial and open-source LLMs and integrate them into enterprise applications.
• Develop LLM-based solutions for text generation, summarization, classification, information extraction, question answering, and conversational AI.
• Implement prompt engineering and optimize prompts for accuracy, relevance, and consistency.
• Work with embeddings, tokenization, context management, model evaluation, and LLM observability.
• Evaluate different LLM models based on quality, latency, cost, security, and business requirements.

Agentic AI

• Design and develop Agentic AI systems and autonomous AI agents.
• Build multi-step AI workflows capable of reasoning, planning, tool usage, and task execution.
• Develop AI agents that interact with APIs, databases, enterprise systems, and external tools.
• Implement agent orchestration, memory, context management, guardrails, and human-in-the-loop workflows.
• Design reliable and scalable agentic architectures for enterprise use cases.

RAG & Knowledge-Based AI

• Design and implement Retrieval-Augmented Generation (RAG) solutions.
• Build document ingestion, chunking, embedding, indexing, retrieval, and generation pipelines.
• Implement semantic search, hybrid search, metadata filtering, and contextual retrieval.
• Work with vector databases and enterprise knowledge repositories.
• Improve RAG accuracy through retrieval optimization, reranking, prompt engineering, and evaluation.
• Implement mechanisms to reduce hallucinations and improve response relevance and grounding.

AI Chatbots

• Develop intelligent AI-powered chatbots and conversational applications.
• Build context-aware, multi-turn conversational experiences.
• Integrate LLMs, RAG, APIs, enterprise data, and business workflows into chatbots.
• Implement conversation history, user context, authentication, guardrails, and fallback mechanisms.
• Monitor chatbot quality, response accuracy, latency, and user experience.

Python & Software Engineering

• Develop production-quality AI/ML applications using Python.
• Build reusable, modular, scalable, and testable AI components.
• Develop REST APIs and integrate AI services with enterprise applications.
• Follow software engineering best practices including Git, testing, CI/CD, code reviews, logging, and documentation.
• Optimize applications for performance, scalability, reliability, and cost.
• Design and develop AI/ML and data processing solutions using Azure Databricks.
• Work with Databricks notebooks, clusters, Spark, Delta Lake, and data pipelines.
• Process and transform large-scale datasets for AI/ML workloads.
• Develop ML workflows and integrate Databricks with Azure services.
• Support model development, experimentation, deployment, and monitoring.
• Optimize Spark/Databricks workloads for performance and cost.
• Implement secure and scalable data and AI architectures on Azure.

Required Technical Skills

Python

Advanced

Advanced

Advanced

Generative AI

Advanced

LLMs

Advanced

Agentic AI / AI Agents

Strong

RAG

Advanced

AI Chatbots

Strong

Strong

NLP

Strong

Prompt Engineering

Strong

Embeddings & Vector Search

Strong

REST APIs

Strong

SQL

Strong

Git

Strong

Preferred Technologies

Experience with some of the following technologies is desirable:

• GenAI Frameworks: LangChain, LlamaIndex, Semantic Kernel or equivalent
• Agentic AI: Agent orchestration frameworks, tool/function calling, multi-agent workflows
• APIs: REST APIs, FastAPI
• MLOps: MLflow and model monitoring/evaluation frameworks

Experience Expectations

5-7 Years

• Strong hands-on experience in Python, AI/ML, and software development.
• Practical experience building and deploying GenAI/LLM applications.
• Experience with RAG and AI chatbot development.
• Working knowledge of Azure Databricks and cloud-based AI solutions.
• Ability to independently develop and productionize AI solutions.

8-10 Years

• Strong expertise in AI/ML and GenAI solution development.
• Experience designing scalable LLM, RAG, chatbot, and Agentic AI architectures.
• Ability to lead technical implementation and mentor engineers.
• Experience taking AI solutions from POC to production.

10-12 Years

• Deep technical expertise in AI/ML, GenAI, LLM, RAG, and Agentic AI.
• Ability to define AI technical strategy and architecture.
• Strong experience with Azure Databricks and enterprise cloud environments.
• Experience leading AI engineering teams and complex AI transformation initiatives.
• Strong stakeholder management and ability to translate business requirements into scalable AI solutions.

Key Responsibilities at Senior Level

• Lead architecture and development of enterprise AI and GenAI solutions.
• Define technical approaches for LLM, RAG, chatbot, and Agentic AI use cases.
• Conduct technical evaluations and proof-of-concepts for emerging AI technologies.
• Establish best practices for prompt engineering, RAG, model evaluation, security, and responsible AI.
• Mentor junior and mid-level AI engineers.
• Collaborate with data scientists, data engineers, software engineers, architects, product managers, and business stakeholders.
• Ensure AI solutions meet requirements for scalability, security, performance, reliability, and cost.
• Stay current with rapidly evolving GenAI and Agentic AI technologies.

Education

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related discipline.

Soft Skills

• Strong analytical and problem-solving abilities.
• Excellent communication and collaboration skills.
• Strong ownership and ability to work independently.
• Ability to explain complex AI concepts to technical and non-technical stakeholders.
• Strong mentoring and leadership capabilities.
• Continuous learning mindset and passion for emerging AI technologies.

Keywords for Recruitment