Applied AI, Cloud Native, GenAI, DevOpsHyderabad- India
Software Specialist Engineer – Applied AI & Cloud Native
Location
Hyderabad- India
Compensation Tier
Mid Level
Category
Applied AI, Cloud Native, GenAI, DevOps
Company Overview
Our client is a leading technology-driven organization focused on building innovative, cloud-native software products and intelligent AI-powered solutions. The organization emphasizes modern engineering practices, scalable architectures, DevSecOps, SRE, and the practical adoption of Generative AI and agentic technologies.
Position Overview
As a Software Specialist Engineer – Applied AI & Cloud Native, you will design, develop, deploy, and optimize scalable software and AI-powered applications. You will work across cloud infrastructure, microservices, application development, GenAI, RAG pipelines, and AI agent orchestration.
The role requires strong software engineering fundamentals combined with hands-on experience in cloud platforms, Infrastructure as Code, containerization, LLM integration, and production-grade AI applications.
Responsibilities
- Design and develop scalable cloud-native applications using microservices, PaaS/FaaS, and serverless architectures.
- Build and deploy AI/ML and Generative AI applications using LLMs, RAG pipelines, vector databases, and AI agents.
- Integrate LLM platforms such as OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, or open-source models.
- Develop AI agent and multi-agent workflows using frameworks such as LangChain, LangGraph, LangFuse, LangSmith, or equivalent technologies.
- Build and manage containerized applications using Docker and Kubernetes.
- Implement Infrastructure as Code using Terraform.
- Develop applications using Python, Go, Java, C#/.NET, Bash, or similar programming languages.
- Implement cloud solutions across Azure, AWS, or GCP, including their AI/ML services.
- Design and implement RAG, prompt engineering, vector search, LLM evaluation, and AI application observability capabilities.
- Apply DevSecOps and SRE practices throughout the software development lifecycle.
- Implement automated unit testing, code quality, security, and continuous integration practices.
- Use tools such as GitHub, Azure DevOps, SonarQube, MLflow, and modern monitoring/observability platforms.
Skills & Experience
- Bachelor's degree in Computer Science, Software Engineering, Data Science, Machine Learning, or a related discipline.
- 6–9 years of software engineering experience, with strong hands-on development experience.
- Strong programming experience in one or more of Python, Go, Java, C#/.NET, or Bash.
- Hands-on experience with Kubernetes, Docker, and Terraform.
- 3+ years of experience building AI/ML, Generative AI, or agentic AI applications.
- Strong hands-on experience with:
- LLM integration
- RAG pipelines
- Prompt engineering
- Vector databases
- LLM evaluations
- AI agent orchestration
- Experience with OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, Vertex AI, or open-source LLMs.
- Experience with LangChain, LangGraph, LangFuse, LangSmith, or equivalent AI/agentic frameworks.
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