Cloud Fullstack Developer remote job for Non US candidates

This is a remote position.

We are seeking a Staff AI/ML solution lead to lead the architecture design and delivery of high-performance enterprise-grade applications. This role combines deep hands-on coding with high-level architectural decision-making. You will work across frontend backend cloud infrastructure database selection and integration layers ensuring our systems are secure scalable and maintainable while enabling long-term technical growth. This hybrid role combines hands-on software engineering devops and architectural leadership enabling the delivery of robust scalable and innovative AI systems.

Key Responsibilities:

• Architecture Leadership Define system architecture integration patterns and technology standards for large-scale web and enterprise applications.
  

• Full Stack Development Build and maintain robust responsive applications using modern frontend frameworks (React Vue streamlit or Angular) and backend services in Python Golang or RUST.
  

• Cloud & Infrastructure Architect cloud-native solutions leveraging AWS with a focus on scalability security and performance. Implement containerized services with Docker and orchestrate deployments using Kubernetes (K8s).
  

• API & Service Design Develop RESTful and GraphQL APIs for internal and external integrations.
  

• DevOps & CI/CD Establish best practices for deployment pipelines automated testing and infrastructure-as-code (Terraform Pulumi).
  

• Performance Optimization Drive system performance tuning load balancing and efficient code design.
  

• Technical Mentorship Coach and mentor engineers conduct design/code reviews and uphold engineering best practices.
  

• Cross-Functional Collaboration Partner with product design and business teams to deliver impactful solutions aligned with company objectives.
  

• Databases: Will be performing database selection and deployment (strong devops experience required)
  

• ML: Experience with both ML and LLM stack design (model hubs vector DBs embedding pipelines). The role required knowledge to deploy end-to-end architecture of ML applications traditional and RAG applications Design of the MLOPS architectures databricks aws and google
  
  ML ops: Strong uderstanding of Agentic AI framework best practices
  
  Clouds: Databricks AWS mandatory
  

  
  

• End to End production level AI/MLl product deployment experience is required
  

Requirements

• At least bachelors in Computer Science mandatory
  

• 10 years in deployment enterprise grade cloud level experience and 5 years in software development
  

• 5 years of experience with Databricks and AWS MLops deployment
  

• This role is more of a software lead and developer with strong Cloud experience to develop infra softwares.
  

• Architect end-to-end agentic pipelines and tools for others to contribute in the team
  

• The role required knowledge to deploy end-to-end architecture of ML applications traditional and RAG applications.
  

• Architect end-to-end AI/ML systems from data ingestion to model deployment.
  

• Define best practices for model serving data pipelines and ML-OPS strategies.
  

• engineering including hands-on model development and architectural design.
  

• Expertise in traditional ML deep learning LLMs embeddings and RAG frameworks.
  

• Strong software engineering skills: Python API development microservices database design and version control (Git).
  

• Experience with cloud platforms (AWS Databricks Google) and containerized deployments (Docker Kubernetes).
  

• Knowledge of ML-OPS CI/CD for AI and production model monitoring.
  

• Strong understanding of software architecture patterns distributed systems and scalable data pipelines.
  

• Databases: Will be performing database selection and deployment (strong devops experience required)
  

Preferred:

Experience with event-driven architectures and messaging systems (NATs Kafka RabbitMQ).

• Familiarity with authentication and authorization frameworks (OAuth2 JWT SSO).
  

• Knowledge of observability and monitoring tools (Prometheus Grafana OpenTelemetry).
  

• Background in designing large-scale enterprise or SaaS platforms.
  

• Python Golang and Rust development experience is preferred
  

• Experience in manufacturing and predictive maintenance is a plus
  

• Background in controls engineering is a plus
  

Soft Skills

• Strong decision-making and problem-solving skills in high-stakes technical environments.
  

• Ability to lead and influence architectural direction across teams.
  

• Excellent communication with both technical and non-technical stakeholders.