Sr. Staff Python Developer (Python,AWS,AI)
HybridHyderabad, Telangana, India
Job Summary
Lead the architecture and development of cloud-native applications, services, and platforms using Python and AWS. Build and manage microservices leveraging Lambda, ECS, S3, Glue, RDS, DynamoDB, EMR, and EKS while designing secure, lightweight Docker images for Python, Spark, and GenAI applications. Drive adoption of engineering best practices including CI/CD, infrastructure as code with Terraform, test automation, and observability. Partner with product, security, architecture, and data science teams to translate business problems into scalable technical solutions. Evaluate emerging AI engineering tools, LLM frameworks, and agentic development platforms to recommend practical adoption paths. You will report to a Senior Manager. Requires 11+ years of software engineering experience with deep AWS expertise and Generative AI implementation patterns.
Required Qualifications
- 11+ years of software engineering experience
- significant experience designing and delivering enterprise-scale systems
- deep experience with AWS, including services such as Lambda, ECS/EKS, API Gateway, S3, IAM, EMR, CloudWatch, Step Functions, EventBridge, RDS/DynamoDB, Bedrock, Glue, or equivalent cloud-native services
- Practical experience with Generative AI concepts and implementation patterns, including LLM integration, prompt engineering, embeddings, vector databases, RAG, AI safety, and model evaluation
- Strong hands-on expertise in Python, including API development, backend services, automation, testing, packaging, and production-grade code quality
- Strong working knowledge of Jupyter notebooks for experimentation, prototyping, and analytical development
- Build application in React, TypeScript, and modern JavaScript (ES6+)
- Languages: Python, SQL, PySpark, typescript
- Cloud: AWS, S3, Lambda, Glue, EMR, SageMaker, Bedrock, IAM, CloudWatch
- AI/GenAI: LLMs, RAG, embeddings, AI agents, model evaluation
- Data: Spark, distributed processing, data lakes, ETL/ELT, batch
- Tools: Jupyter, Git, CI/CD, Docker, Kubernetes, Terraform or CloudFormation
- Engineering: APIs, microservices, observability, testing, security, architecture design
- Lead the architecture and development of cloud-native applications, services, and platforms using Python and AWS
- Build and manage cloud-native microservices leveraging AWS services such as Lambda, ECS, S3, Glue, RDS/DynamoDB, EMR, glue and EKS
- Provide technical leadership across engineering teams, driving design reviews, architecture decisions, coding standards, and operational excellence
- Partner with product, security, architecture, data science, and platform teams to translate business problems into scalable technical solutions
- Develop reusable frameworks, libraries, APIs, and automation patterns that accelerate engineering delivery
- Drive adoption of engineering best practices including CI/CD, infrastructure as code, test automation, observability, secure SDLC
- Build and optimize large-scale distributed data processing solutions using Apache Spark, PySpark, SQL, and cloud data services
- Evaluate emerging AI engineering tools, LLM frameworks, model providers, and agentic development platforms, recommending practical adoption paths
- Design, build, and maintain secure, lightweight Docker images for Python, Spark, and GenAI applications
- Build and maintain Infrastructure as Code using Terraform for AWS cloud resources and platform components
- #LI-Onsite
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