AI Developer - Python + AWS Bedrock
Summary
Permanent-remote 12-month contract for an AI Developer with 5+ years of Python/AI-ML experience. Day to day: building LLM/RAG and ML solutions on AWS Bedrock, developing FastAPI/Flask APIs and microservices, and handling AWS infra (Lambda, SageMaker, ECS/EKS), Docker/Kubernetes, CI/CD, and data pipelines. Budget listed at 90k monthly; immediate joiners only.
This is a remote position.
Job Description: AI Developer (5+ Years Experience)
Budget: 90k monthly
Contract Duration- 12 months
Work Mode- permanent Remote
Yrs. Of Experience: 5+ yrs
Immediate Joiners only
Mandatory Skills :
1. Langchain
2. Aws lambda, Sns, sqs, api gateway
3. Fast api
4. Pg vector database
5. Postman
5. Git
We are seeking a skilled AI Developer with expertise in Python, AI/ML development, AWS Bedrock, and cloud computing. The ideal candidate should have experience working with machine learning frameworks, data engineering, and cloud infrastructure. This role requires strong problem-solving skills, AI model optimization capabilities, and hands-on experience in deploying scalable AI solutions.
Job Responsibilities:
1. AI & Machine Learning Development:
• Develop, train, fine-tune, and deploy machine learning models using TensorFlow, PyTorch, scikit-learn, and NumPy.
• Work with Large Language Models (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.
2. 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.
3. Cloud & DevOps:
• Deploy AI solutions using AWS Bedrock and integrate with services like 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.
4. 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.
5. Collaboration & Documentation:
• Collaborate with data scientists, engineers, and product managers to integrate AI into applications.
• Write clear documentation for AI models, workflows, and deployment processes.
• Explain AI concepts to non-technical stakeholders when required.
Requirements
Job Requirements:
Essential Requirements:
✅ Programming & AI Development:
• 5+ years of experience in Python development with AI/ML focus.
• Proficiency in AI/ML frameworks like 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 other AWS 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.
✅ Version Control & Collaboration:
• Proficiency in Git and best practices for collaborative development.
• Familiarity with project management tools like Jira or Trello.
Soft Skills:
✔️ Strong problem-solving and analytical thinking.
✔️ Excellent communication skills to explain AI models and technical concepts.
✔️ Ability to work collaboratively in cross-functional teams.
✔️ Adaptability to learn and implement emerging AI/ML technologies.
Skills
- AI
- Airflow
- API
- API Gateway
- AWS
- AWS Bedrock
- Aws Glue
- CI/CD
- Cloud
- Computer Vision
- Containerization
- Data Engineering
- Data Pipelines
- DevOps
- Docker
- DynamoDB
- ECS
- EKS
- ETL
- FastAPI
- Flask
- Git
- IAM
- Jira
- Kubernetes
- Lambda
- LangChain
- LLM
- Machine Learning
- Microservices
- Model Deployment
- MongoDB
- MySQL
- Neural Networks
- NLP
- NoSQL
- NumPy
- OOP
- PostgreSQL
- Postman
- Python
- PyTorch
- RAG
- REST
- S3
- SageMaker
- scikit-learn
- SNS
- Spark
- SQS
- TensorFlow
- Trello
- Vector Databases
- Version Control