Senior Software Engineer

Clarus Advisers; Hyderabad; On-site; INR 2,800,000 - 4,000,000; Full time

Job summary

Clarus Advisers is seeking a Software Specialist Engineer – Applied AI & Cloud Native in Hyderabad to design, develop, deploy, and optimize scalable AI-powered software. You will work across cloud platforms, microservices, and GenAI pipelines to deliver production-grade AI solutions.

The role requires hands-on experience with Kubernetes, Docker, Terraform, and AI/ML frameworks, plus strong coding skills in Python/Go/Java/C# and cloud-native engineering practices.

Qualifications

• 6–9 years of software engineering experience with hands‑on development.
• Strong programming in one or more of Python, Go, Java, C#/.NET, or Bash.
• 3+ years building AI/ML, Generative AI, or agentic AI apps.

Responsibilities

• Design and develop scalable cloud-native apps using microservices and serverless architectures.
• Build AI/ML and Generative AI apps using LLMs, RAG, vector DBs, and AI agents.
• Integrate LLM platforms (OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, Vertex AI).
• Develop AI agent workflows using LangChain, LangGraph, LangFuse, LangSmith, or equivalents.
• Containerize apps with Docker and Kubernetes; implement IaC with Terraform.
• Develop across Azure, AWS, GCP and their AI/ML services; implement DevSecOps and SRE practices.
• Ensure code quality with automated testing, CI/CD, and observability tooling.
• Create and maintain architecture diagrams, data models, and documentation.

Skills

Python

Go

Java

C#/.NET

Bash

Kubernetes

Docker

Terraform

AI/ML

LLM integration

Education

Bachelor's degree in Computer Science / Software Engineering / Data Science or related

Tools

GitHub

Azure DevOps

SonarQube

MLflow

LangChain/LangGraph/LangFuse/LangSmith

Job description

Company Overview

Our client is a leading technology-driven organization focused on building innovative, cloud-native software products and intelligent AI-powered solutions.

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

• 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.
• Strong 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.
• Bachelor's degree in Computer Science, Software Engineering, Data Science, Machine Learning, or a related discipline.