Role Overview

We are seeking a skilled AI Developer with expertise in Python, AI/ML development, AWS Bedrock, and cloud computing. Experience in machine learning frameworks, data engineering, and cloud infrastructure is essential. Requires strong problem-solving, model optimization, and hands-on experience in deploying scalable AI solutions.

Responsibilities

AI & Machine Learning Development
- Develop, train, fine-tune, and deploy ML models using TensorFlow, PyTorch, scikit-learn, and NumPy.
- Work with LLMs, Retrieval-Augmented Generation (RAG) Systems, NLP, and computer vision.
- Integrate and utilize pre-trained AI models, including those in AWS Bedrock.
- Optimize AI model performance, scalability, and efficiency.
Backend Development & API Integration
- Design and develop RESTful APIs using Flask or FastAPI for AI model deployment.
- Implement robust microservices architecture for AI-based applications.
- Ensure secure, efficient, and scalable backend AI solutions.
Cloud & DevOps
- Deploy AI solutions using AWS Bedrock and integrate with S3, Lambda, SageMaker, ECS/EKS, and IAM.
- Manage cloud infrastructure provisioning, cost optimization, and security policies.
- Work with CI/CD pipelines for seamless AI model deployment.
- Utilize Docker and Kubernetes for containerized deployments.
Database & Data Engineering
- Design, query, and optimize relational (PostgreSQL, MySQL) and NoSQL (DynamoDB, MongoDB) databases.
- Develop and automate data pipelines using Apache Airflow, AWS Glue, or Spark.
- Implement ETL processes for AI data handling.

Requirements

Essential Programming & AI Development

5+ years of experience in Python development with AI/ML focus.
Proficiency in ML frameworks: TensorFlow, PyTorch, and scikit-learn.
Experience in neural networks, NLP, LLMs, RAG, and computer vision.

Backend & API Development

Experience in RESTful API development using Flask or FastAPI.
Strong knowledge of OOP, functional programming, and microservices architecture.

Cloud & DevOps

Experience with AWS Bedrock and services (S3, Lambda, SageMaker, ECS/EKS, IAM).
Hands-on experience with containerization (Docker) and orchestration (Kubernetes).
Understanding of CI/CD pipelines and DevOps practices.

Data Engineering & Databases

Strong knowledge of PostgreSQL, MySQL, DynamoDB, and MongoDB.
Experience with data pipelines, ETL processes, and Apache Airflow/Spark/AWS Glue.

SOFT SKILLS

Strong problem-solving and analytical thinking.
Excellent communication to explain AI models and technical concepts.
Ability to work collaboratively in cross-functional teams.
Adaptability to learn and implement emerging AI/ML technologies.