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Applied AI Engineer – Software Specialist Engineer II

Clarus

Bengaluru / Hyderabad / Gurugram

6-9 years

2 days ago

$49.4K–69.9K/yr

Full time

Onsite

Skills Required LLM

RAG

LangChain

Gen AI

OpenAI

Anthropic

Azure OpenAI

LangGraph

LangFuse

LangSmith

AI/ML

AWS Bedrock

Vertex AI

Python

SQL

Description Applied AI Engineer – Software Specialist Engineer II role focused on building production-grade Generative AI and agentic applications. The position combines software engineering, cloud-native architecture, DevSecOps, and AI-augmented development.

Company: Clarus

Role: Applied AI Engineer – Software Specialist Engineer

Location: Bengaluru, Hyderabad, Gurugram – India

Experience

- 6–9 years of overall software engineering experience
- 3+ years of hands-on experience building AI/ML, Generative AI, and/or agentic applications
- Solid programming experience in Python and SQL
- Experience with one or more of C#/.NET, Java, NodeJS, Angular, or React
- Solid hands-on experience with LLMs, RAG, prompt engineering, vector databases, and LLM evaluation
- Experience integrating OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, Vertex AI, or open-source LLMs
- Experience with LangChain, LangGraph, or equivalent agent orchestration frameworks
- 3+ years of experience with Azure, AWS, or GCP and cloud-native engineering
- Experience with microservices, PaaS/FaaS, APIs, Infrastructure as Code, and CI/CD
- Strong understanding of OOP/OOD, data structures, algorithms, system design, and software testing
- Experience with DevSecOps, SRE, XP/Lean,



GitHub/Azure DevOps, and SonarQube

Qualification

- Bachelor's degree in Computer Science
- Bachelor's degree in Software Engineering
- Bachelor's degree in Data Science
- Bachelor's degree in Machine Learning
- Bachelor's degree in a related discipline

Responsibilities

- Design and develop production-ready Generative AI and agentic AI applications
- Build LLM-powered solutions using cloud and model platforms
- Develop RAG pipelines, prompt engineering workflows, vector search, and knowledge-based AI applications
- Build and orchestrate AI agents with agent framework tools
- Develop scalable cloud-native applications on Azure, AWS, or GCP
- Implement microservices, PaaS/FaaS architectures, APIs, and application-level infrastructure as code
- Apply AI/ML evaluation, monitoring, tracing, and observability practices
- Develop maintainable software using OOP/OOD, DSA, testing, and code instrumentation
- Collaborate on architecture and technical designs using business and system diagrams
- Implement CI/CD, DevSecOps, SRE, security, and quality engineering practices
- Use engineering platforms such as GitHub, Azure DevOps, SonarQube, and MLflow
- Apply cost-aware engineering and FinOps principles to cloud and AI workloads




- Contribute to AI-augmented and spec-driven software development
- Translate business requirements into scalable AI solutions with cross-functional teams

Nice To Have

- Knowledge of PyTorch/TensorFlow is desirable

More Skills Applied AI, Azure, AWS, prompt engineering, vector databases, agentic applications, microservices, PaaS, FaaS, APIs, Infrastructure as Code, CI/CD, AI/ML evaluation, monitoring, tracing, observability, OOP, OOD, DSA, testing, code instrumentation, business context, sequence diagrams, activity diagrams, state diagrams, entity relationship diagrams, data-flow diagrams, DevSecOps, SRE, security, quality engineering, GitHub, Azure DevOps, SonarQube, MLflow, FinOps, AI-augmented development, spec-driven software development, cloud-native architecture

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