Software Engineer - Generative AI

Description :

Key Responsibilities :

Software Engineering & Cloud Infrastructure (Primary Focus) :

- Design, develop, and optimize cloud-native backend services using Python and/or Node.js for AI-driven applications on AWS or Azure

- Build and deploy scalable architectures using serverless computing, containers, and managed cloud services

- Develop and manage Infrastructure as Code (IaC) using Terraform, AWS CloudFormation, or Azure ARM templates to automate and standardize cloud deployments

- Implement and maintain CI/CD pipelines for AI model deployments, backend services, and automated testing using tools such as GitHub Actions, Azure DevOps, or similar

- Design and develop high-performance APIs and microservices (FastAPI, gRPC, REST) to serve AI capabilities such as LLM inference, agent workflows, and AI pipelines

- Optimize systems for security, scalability, latency, reliability, and cost efficiency

Reliability, Monitoring & Observability :

- Ensure high availability and reliability of AI systems through monitoring, logging, and alerting

- Implement observability solutions using Prometheus, CloudWatch, Azure Monitor, or equivalent tools

- Troubleshoot production issues and drive continuous improvements in system stability and performance

Collaboration & Best Practices :

- Collaborate with data scientists, ML engineers, and product teams to productionize AI models and workflows

- Participate in architectural discussions and contribute to cloud and AI platform roadmaps

- Follow best practices in software design, security, and DevOps

Required Skills & Qualifications :

- 710 years of overall software engineering experience

- Strong proficiency in Python and/or Node.js for backend development

- Hands-on experience with AWS or Azure cloud platforms

- Proven experience in cloud-native architectures, including serverless and container-based systems (Docker, Kubernetes)

- Expertise in Infrastructure as Code (Terraform, CloudFormation, ARM templates)

- Experience building and deploying CI/CD pipelines

- Strong experience with API and microservices development (FastAPI, gRPC, REST)

- Knowledge of monitoring, logging, and observability tools (Prometheus, CloudWatch, etc.)

- Solid understanding of security best practices in cloud environments

Preferred Qualifications :

- Experience working with Generative AI / LLM-based systems

- Familiarity with AI model serving, inference optimization, and agent frameworks

- Knowledge of MLOps practices and AI lifecycle management

- Experience with cost optimization strategies in cloud environments

- Exposure to multi-cloud or hybrid architectures