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Role: Senior Software Engineer
Position Type: Full-Time Contract (40hrs/week)
Contract Duration: Long Term
Work Schedule: 8 hours/day (Mon-Fri)
Location: Hybrid - Wed/Thursday to be in onsite in Hyderabad, India
We are seeking a Senior AI Software Engineer with deep expertise in Python, cloud-native application development, and Generative AI technologies. This role focuses on building scalable AI-powered applications, LLM integrations, Agentic AI solutions, and distributed microservices on AWS. The ideal candidate has strong experience developing production-grade APIs, integrating OpenAI or similar LLM platforms, implementing RAG pipelines, and designing highly scalable backend systems.
Key Responsibilities
Design and develop scalable, secure, and cloud-native applications on AWS.
Build and maintain distributed applications using Python, Flask, Django, and AsyncIO.
Design REST APIs, microservices, and event-driven architectures.
Develop and support MLOps platforms using AWS SageMaker, Kubeflow, or MLflow.
Lead cloud modernization initiatives following AWS Well-Architected Framework principles.
Design and maintain CI/CD pipelines and deployment automation.
Integrate applications with Kafka, RabbitMQ, or Amazon SQS.
Monitor, troubleshoot, and optimize distributed production systems.
Conduct architecture reviews, code reviews, and mentor development teams.
Collaborate with architects, product managers, and global engineering teams.
Establish engineering standards, documentation, and best practices.
Required Qualifications
Bachelor's degree in Computer Science or related discipline.
8+ years of software engineering experience.
5+ years of hands-on AWS experience.
Strong Python development experience.
Experience with Flask, Django, or AsyncIO.
Experience developing APIs and microservices.
Strong understanding of distributed systems.
Experience with AWS services such as EKS, ECS, Lambda, S3, RDS, Aurora, and Fargate.
Experience implementing CI/CD pipelines using Jenkins, CodePipeline, CodeDeploy, Harness, or similar tools.
Experience with Kafka, RabbitMQ, or Amazon SQS.
Experience with AWS SageMaker, Kubeflow, or MLflow.
Experience working within Agile environments.
Strong communication and technical leadership skills.
Work arrangement
No
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