Lead Developer, Python Development

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What Well Bring:

What Youll Bring:

• Design develop and maintain scalable secure applications using Python and/Java
• Lead endtoend SDLC activities: requirements analysis architectural design development testing deployment and ongoing support.
• Define and implement software architecture patterns (microservices event-driven design layered architecture domain-driven design).
• Build deploy and optimize applications on AWS and/or GCP (Compute Storage IAM Networking Serverless CI/CD).
• Develop and integrate RESTful APIs microservices and distributed systems.
• Implement AI/ML features by using cloud-native AI services or integrating custom ML models (e.g. AWS SageMaker GCP Vertex AI or opensource frameworks).
• Participate in architectural reviews make technology recommendations and drive technical decisionmaking.
• Conduct code reviews enforce coding best practices and mentor junior team members.
• Troubleshoot production issues identify root causes and deliver reliable fixes.
• Maintain clear and comprehensive technical documentation.

• Minimum 6 years of handson experience in Python and/or Java.
• Strong understanding of SDLC methodologies including Agile/Scrum CI/CD DevOps practices.
• Solid grasp of software architecture concepts: scalability performance security modularity design patterns.
• Experience with cloud platforms:
  • AWS: EC2 Lambda S3 RDS DynamoDB EKS API Gateway SageMaker
  • GCP: Compute Engine Cloud Run GKE Cloud Functions BigQuery Vertex AI
• Practical exposure to AI in software development such as:
  • Integrating LLMbased features
  • Using AI APIs (AWS Bedrock GCP Vertex AI OpenAI etc.)
  • Building ML pipelines or inference workflows
• Experience with relational and NoSQL databases.
• Strong understanding of containerisation and orchestration (Docker Kubernetes).
• Good knowledge of CI/CD tools (Jenkins GitHub Actions GitLab CI Argo etc.).
• Excellent problem-solving debugging and design skills.

Impact Youll Make:

Good to Have

• Experience with messaging systems (Kafka Pub/Sub RabbitMQ).
• Exposure to infrastructureascode (Terraform CloudFormation).
• Hands-on experience with monitoring and observability tools (Prometheus Grafana CloudWatch).
• Security best practices for cloudnative workloads.
• Knowledge of MLOps concepts.

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