Artificial Intelligence Engineer - Python Programming (5-8 yrs)

Job Summary :

We are seeking a highly motivated and experienced Artificial Intelligence Engineer with a proven track record in developing, optimizing, and deploying AI/ML solutions, particularly leveraging Large Language Models (LLMs) and Retrieval Augmented Generation (RAG) systems.

The ideal candidate possesses a deep understanding of AI/ML principles, strong programming skills in Python, and hands-on experience with cloud platforms, especially AWS Bedrock.

This role requires a proactive individual who can translate business needs into technical solutions, work effectively in a collaborative environment, and contribute to the advancement of our AI capabilities.

You will be instrumental in building and scaling our AI infrastructure, ensuring performance, reliability, and security.

Key Responsibilities :

AI & Machine Learning Development :

- Design, develop, train, and deploy machine learning models using state-of-the-art techniques and frameworks like TensorFlow, PyTorch, and scikit-learn.

- Deep expertise in working with LLMs, including fine-tuning, prompt engineering, and performance optimization.

- Develop and implement RAG systems, integrating external knowledge sources to enhance LLM capabilities.

- Experience in Natural Language Processing (NLP) tasks such as text classification, sentiment analysis, named entity recognition, and machine translation.

- Proficiency in Computer Vision tasks, including image classification, object detection, and image segmentation (preferred).

- Conduct rigorous model evaluation and validation, ensuring accuracy, robustness, and generalizability.

- Continuously research and evaluate new AI/ML techniques and technologies to improve our solutions.

Backend & API Development :

- Design and develop robust and scalable RESTful APIs using Flask or FastAPI for seamless integration of AI models into applications.

- Implement secure authentication and authorization mechanisms for API access.

- Design and implement microservices architecture for modularity, scalability, and maintainability.

- Experience with asynchronous task queues (e.g, Celery, Redis Queue) for efficient processing.

Cloud & DevOps :

- Deploy and manage AI solutions on AWS Bedrock, leveraging its various services and features.

- Integrate AI models with other AWS services such as S3, Lambda, SageMaker, ECS/EKS, and API Gateway.

- Implement Infrastructure as Code (IaC) using tools like Terraform or CloudFormation.

- Manage CI/CD pipelines using tools like Jenkins, GitLab CI, or AWS CodePipeline.

- Implement containerization and orchestration using Docker and Kubernetes for scalable and portable deployments.

- Monitor and optimize the performance and cost of cloud-based AI solutions.

Data Engineering & Databases :

- Work with both relational databases (PostgreSQL, MySQL) and NoSQL databases (DynamoDB, MongoDB) to store and retrieve data efficiently.

- Develop and optimize data pipelines for data ingestion, processing, and transformation using tools like Apache Airflow, AWS Glue, or Spark.

- Implement ETL processes for preparing data for machine learning model training.

- Experience with data quality management and data governance practices.

Collaboration & Documentation :

- Collaborate effectively with cross-functional teams, including product managers, engineers, and data scientists, to define requirements and deliver solutions.

- Clearly document AI workflows, model details, and technical designs.

- Communicate complex technical concepts effectively to both technical and non-technical stakeholders.

- Actively participate in code reviews and knowledge sharing sessions.

Requirements :

- AI/ML Development : 5+ years of professional experience in Python development with a strong focus on AI/ML frameworks (TensorFlow, PyTorch, scikit-learn). Demonstrable experience with LLMs and RAG systems is crucial.

- Backend & API : Proven experience in building RESTful APIs using Flask/FastAPI, strong understanding of Object-Oriented Programming (OOP) principles, and experience with microservices architecture.

- Cloud & DevOps : Hands-on experience with AWS Bedrock and other AWS services. Proficiency in containerization (Docker, Kubernetes) and CI/CD practices is essential. Experience with IaC is highly desirable.

- Data Engineering : Strong SQL and NoSQL expertise, experience with ETL processes, and data pipeline management using tools like Airflow, Glue, or Spark.

- Collaboration : Proficiency with Git, experience with project management tools (Jira/Trello), and excellent communication skills