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.
- Optimize application and cloud infrastructure costs and demonstrate FinOps awareness.
- Create and interpret architecture and engineering artifacts including BCDs, sequence diagrams, activity diagrams, state diagrams, ER/data models, and data-flow diagrams.
- Apply OOP/OOD, data structures, algorithms, code instrumentation, and AI-augmented spec-driven development.
- Collaborate with engineering, product, architecture, and AI/ML teams to deliver high-quality products rapidly.

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.
- Experience with Azure, AWS, or GCP and cloud-native application development.
- Knowledge of PaaS, FaaS/serverless, microservices, and application-level Infrastructure as Code.
- Experience with PyTorch, TensorFlow, or equivalent ML frameworks is desirable.
- Robust understanding of OOP/OOD, data structures, algorithms, software architecture, and system design.
- Experience with DevSecOps, SRE, CI/CD, GitHub, Azure DevOps, and SonarQube.
- Experience with automated/unit testing frameworks.
- Exposure to MLflow and monitoring/observability tools is an advantage.
- Understanding of FinOps and cloud cost optimization.
- Strong understanding of software architecture diagrams and technical documentation.
- Ability to work in an AI-augmented, spec-driven software development environment.

📌 Software Specialist Engineer – Applied AI & Cloud Native (Hyderabad)
🏢 Clarus Advisers
📍 Hyderabad