AI Engineer (Generative AI & LLMs)

Job Description

We are seeking an innovative and highly skilled AI Engineer (Generative AI & Large Language Models) to join our growing AI Engineering team. In this role, you will design, develop, deploy, and optimize AI-powered applications using Large Language Models (LLMs), Generative AI, and modern machine learning frameworks. You will collaborate with data scientists, software engineers, product managers, and business stakeholders to build intelligent, scalable, and production-ready AI solutions that enhance customer experiences and drive business innovation.

The ideal candidate has hands-on experience with LLMs, prompt engineering, Retrieval-Augmented Generation (RAG), vector databases, cloud platforms, and modern AI development frameworks. You should be passionate about staying current with advancements in AI technologies while building secure, reliable, and scalable AI applications.

Key Responsibilities

• Design, develop, and deploy AI-powered applications using Large Language Models (LLMs) and Generative AI technologies.
• Build Retrieval-Augmented Generation (RAG) pipelines using vector databases and enterprise knowledge sources.
• Develop intelligent chatbots, AI assistants, document processing systems, and workflow automation solutions.
• Design effective prompts and prompt engineering strategies to improve AI model accuracy and reliability.
• Integrate foundation models through APIs and open-source frameworks into production applications.
• Fine-tune, evaluate, and optimize AI models for business-specific use cases where appropriate.
• Develop scalable AI microservices and RESTful APIs for enterprise applications.
• Build data preprocessing and embedding pipelines for text, documents, and structured data.
• Monitor AI application performance, latency, quality, and operational metrics.
• Implement AI safety, security, governance, and responsible AI best practices.
• Collaborate with Data Scientists, Machine Learning Engineers, and Software Engineers throughout the AI development lifecycle.
• Deploy AI solutions on cloud platforms such as AWS, Microsoft Azure, or Google Cloud.
• Optimize infrastructure costs and inference performance for production AI workloads.
• Perform model evaluation, benchmarking, and continuous improvement using automated testing and feedback.
• Document AI architectures, technical designs, deployment procedures, and operational guidelines.
• Stay current with emerging AI technologies, research papers, frameworks, and industry trends.

Required Qualifications

• Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related technical field (or equivalent practical experience).
• 3+ years of experience in software engineering, machine learning, or AI application development.
• Strong proficiency in Python and modern software development practices.
• Experience developing applications using Large Language Models (LLMs) and Generative AI technologies.
• Hands-on experience with AI orchestration frameworks such as LangChain, LlamaIndex, or similar tools.
• Experience building Retrieval-Augmented Generation (RAG) solutions.
• Familiarity with vector databases such as Pinecone, Chroma, FAISS, Weaviate, or Milvus.
• Strong understanding of REST APIs, microservices, and distributed systems.
• Experience working with cloud platforms including AWS, Microsoft Azure, or Google Cloud.
• Strong knowledge of Git, Docker, CI/CD pipelines, and software deployment practices.
• Excellent analytical, communication, and problem-solving skills.

Preferred Qualifications

• Master’s degree in Artificial Intelligence, Computer Science, Data Science, or a related field.
• Experience with transformer architectures and deep learning frameworks such as PyTorch or TensorFlow.
• Knowledge of MLOps practices, model deployment, and AI lifecycle management.
• Experience with Kubernetes and container orchestration.
• Familiarity with SQL, NoSQL databases, and data engineering concepts.
• Understanding of AI governance, security, privacy, and compliance requirements.
• Experience deploying enterprise-scale AI solutions in production.
• Contributions to open-source AI projects or published AI research are a plus.

Technical Skills

Programming Languages

• Python
• SQL
• JavaScript (preferred)
• TypeScript (preferred)

AI & Machine Learning

• Large Language Models (LLMs)
• Generative AI
• Prompt Engineering
• Retrieval-Augmented Generation (RAG)
• Fine-Tuning
• Embeddings
• AI Agents
• Model Evaluation
• Natural Language Processing (NLP)

Frameworks & Libraries

• LangChain
• LlamaIndex
• Hugging Face Transformers
• PyTorch
• TensorFlow
• Scikit-learn
• FastAPI
• Flask

Vector Databases

• Pinecone
• Chroma
• FAISS
• Weaviate
• Milvus

Cloud Platforms

• AWS
• Microsoft Azure
• Google Cloud Platform (GCP)

DevOps & MLOps

• Docker
• Kubernetes
• Git
• GitHub Actions
• MLflow
• CI/CD Pipelines

Databases

• PostgreSQL
• MongoDB
• Redis

Soft Skills

• Strong analytical and critical thinking abilities.
• Excellent problem-solving skills.
• Effective verbal and written communication.
• Ability to collaborate in cross-functional teams.
• Strong organizational and time-management skills.
• Adaptability in a fast-paced, evolving technology environment.
• Passion for continuous learning and innovation.

Preferred Certifications

• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure AI Engineer Associate
• Databricks Certified Machine Learning Professional
• TensorFlow Developer Certificate