AI Engineer - Job Description
Raas Infotek LLC
yesterday
Role details
Contract type
Permanent contract Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
EnglishJob location
Tech stack
Java
API
Artificial Intelligence
Airflow
Amazon Web Services (AWS)
Computer Vision
Azure
Big Data
Cloud Computing
Cloud Engineering
Continuous Integration
Data Governance
Data Transformation
DevOps
Hadoop
Python
Machine Learning
Natural Language Processing
NoSQL
Scrum
Recommender Systems
TensorFlow
Standard Sql
Speech Recognition
Google Cloud Platform
Enterprise Software Applications
Data Ingestion
PyTorch
Large Language Models
Multi-Agent Systems
Prompt Engineering
Spark
Deep Learning
Generative AI
Keras
AI Platforms
Scikit Learn
Kubernetes
Information Technology
HuggingFace
Kafka
Machine Learning Operations
REST
Software Version Control
Docker
Jenkins
Microservices
Job description
We are seeking a highly skilled AI Engineer with 12+ years of experience in designing, developing, and deploying Artificial Intelligence and Machine Learning solutions for enterprise applications. The ideal candidate will have deep expertise in Machine Learning, Deep Learning, Generative AI, Large Language Models (LLMs), MLOps, and cloud-based AI platforms. This role requires collaboration with cross-functional teams to build scalable AI-driven solutions that support business innovation and digital transformation initiatives., * Design, develop, and deploy AI/ML models and intelligent applications for enterprise use cases.
- Build and optimize machine learning, deep learning, NLP, and Generative AI solutions.
- Develop end-to-end AI pipelines including data ingestion, preprocessing, model training, validation, deployment, and monitoring.
- Implement Large Language Model (LLM) solutions, Prompt Engineering, Retrieval-Augmented Generation (RAG), and AI chatbot applications.
- Work with structured and unstructured datasets to develop predictive and analytical models.
- Deploy AI solutions on cloud platforms such as AWS, Azure, or Google Cloud Platform (Google Cloud Platform).
- Implement MLOps best practices for model versioning, monitoring, retraining, and CI/CD automation.
- Collaborate with data scientists, software engineers, product owners, and business stakeholders to deliver AI-based solutions.
- Optimize AI model performance, scalability, reliability, and inference efficiency.
- Develop APIs and microservices for AI model integration into enterprise applications.
- Ensure compliance with data governance, security, and responsible AI standards.
- Conduct research on emerging AI technologies and recommend innovative solutions.
- Mentor junior engineers and provide technical leadership to AI/ML teams.
- Participate in Agile/Scrum ceremonies and support project delivery activities.
Requirements
- 12+ years of overall IT experience with strong expertise in AI/ML Engineering.
- Hands-on experience in Machine Learning, Deep Learning, NLP, and Generative AI technologies.
- Strong proficiency in Python, Java, or Scala.
- Experience with AI/ML frameworks such as TensorFlow, PyTorch, Keras, Scikit-learn, or Hugging Face Transformers.
- Expertise in LLMs, Prompt Engineering, LangChain, RAG architecture, vector databases, and AI orchestration frameworks.
- Strong understanding of MLOps tools such as MLflow, Kubeflow, Docker, Kubernetes, Jenkins, or Airflow.
- Experience with cloud AI services in AWS, Azure, or Google Cloud Platform.
- Knowledge of SQL, NoSQL databases, and big data technologies such as Spark, Hadoop, or Kafka.
- Experience building REST APIs and microservices architectures.
- Familiarity with DevOps, CI/CD pipelines, and automation processes.
- Strong analytical, problem-solving, and communication skills.
- Experience working in Agile/Scrum development environments., * Experience with Generative AI applications and enterprise AI transformation projects.
- Knowledge of Responsible AI, AI governance, and ethical AI practices.
- Exposure to Computer Vision, Speech Recognition, or Recommendation Systems is a plus.
- AI/ML or Cloud certifications preferred.
- Experience with enterprise-scale distributed AI systems is highly desirable., * Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or related field.
- Master's degree preferred.