Generative AI Engineer - LLM & RAG Implementation

Gen AI Engineer

Experience : 5-8 Years

Location : Hybrid

Employment Type : Full-Time

About the Role :

We are seeking a highly skilled Gen AI Engineer to design, develop, and deploy next-generation Artificial Intelligence solutions leveraging Machine Learning, Deep Learning, Large Language Models (LLMs), Natural Language Processing (NLP), and Generative AI technologies.

The ideal candidate will possess strong experience in building AI-powered applications, implementing enterprise-grade Generative AI solutions, fine-tuning foundation models, and deploying scalable machine learning systems. This role offers an opportunity to work on cutting-edge AI initiatives that drive business transformation, intelligent automation, knowledge management, and advanced analytics.

The candidate will collaborate closely with Data Scientists, Product Teams, Engineering Teams, and Business Stakeholders to deliver innovative AI-driven solutions that create measurable business value.

Key Responsibilities :

1. Generative AI Solution Development :

- Design, develop, and deploy enterprise-grade Generative AI applications.

- Build AI-powered assistants, chatbots, copilots, knowledge management systems, and intelligent automation solutions.

- Develop and implement Large Language Model (LLM)-based solutions for various business use cases.

- Optimize prompt engineering strategies and improve model performance.

- Evaluate emerging Generative AI technologies and recommend innovative approaches.

2. Machine Learning & Deep Learning :

- Design and implement machine learning and deep learning models.

- Build predictive analytics and AI-driven decision-support systems.

- Develop model training, validation, testing, and deployment pipelines.

- Apply advanced machine learning algorithms to solve complex business challenges.

- Continuously improve model accuracy, efficiency, and scalability.

3. Natural Language Processing (NLP) :

- Develop NLP-based solutions for text classification, summarization, semantic search, entity extraction, sentiment analysis, and conversational AI.

- Implement language understanding and language generation systems.

- Work with structured and unstructured data sources.

- Develop intelligent search and knowledge retrieval capabilities.

4. LLM & RAG Implementation :

- Build and optimize Retrieval-Augmented Generation (RAG) architectures.

- Integrate Large Language Models with enterprise data sources.

- Develop vector search and semantic retrieval frameworks.

- Work with embedding models and vector databases to enhance AI application performance.

- Improve response quality, context management, and knowledge grounding.

5. AI Engineering & Model Deployment :

- Deploy AI and ML models into production environments.

- Build scalable APIs and AI services for enterprise applications.

- Collaborate with engineering teams to ensure production readiness.

- Implement model monitoring, governance, observability, and lifecycle management.

- Optimize AI solutions for performance, scalability, security, and cost efficiency.

6. Stakeholder Collaboration :

- Partner with business stakeholders to understand requirements and identify AI opportunities.

- Translate business problems into scalable AI and machine learning solutions.

- Present technical solutions and recommendations to business and leadership teams.

- Work collaboratively across product, engineering, analytics, and business functions.

Required Skills & Experience :

- 5- 8 years of experience in Machine Learning, Artificial Intelligence, Data Science, or Advanced Analytics.

- Strong expertise in Generative AI, Machine Learning, and Deep Learning.

- Hands-on experience with Large Language Models (LLMs) and NLP solutions.

- Advanced proficiency in Python and AI development frameworks.

- Experience deploying AI models in production environments.

- Strong understanding of model evaluation, optimization, and deployment best practices.

Mandatory Skills :

- Generative AI

- Machine Learning

- Deep Learning

- Large Language Models (LLMs)

- Natural Language Processing (NLP)

- Python, AI Model Development

- Model Deployment

- Prompt Engineering

- AI Frameworks.

Why Join Us :

- Opportunity to work on cutting-edge Generative AI and Machine Learning initiatives.

- Exposure to enterprise-scale AI transformation programs.

- Collaborate with industry experts in AI, Data Science, and Product Engineering.

- Build impactful AI solutions that drive business innovation and growth.

(ref:hirist.tech)