Applied AI, GenAI, Python, Azure/AWSBengaluru, Hyderabad, Gurugram – India
Applied AI Engineer – Software Specialist Engineer
Location
Bengaluru, Hyderabad, Gurugram – India
Compensation Tier
Mid Level
Category
Applied AI, GenAI, Python, Azure/AWS
Company Overview
Our client is a leading technology organization focused on building modern, cloud-native software and AI-driven solutions. The organization combines software engineering, cloud technologies, and applied AI to deliver scalable, secure, and high-quality products.
Position Overview
As an Applied AI Engineer – Software Specialist Engineer II, you will design, develop, and deploy production-grade AI/GenAI applications. You will work across the full software development lifecycle, integrating LLMs, RAG pipelines, vector databases, AI agents, and cloud AI services.
The role requires strong software engineering fundamentals combined with practical experience in Generative AI, agentic applications, cloud-native architecture, DevSecOps, and AI-augmented development practices.
Responsibilities
- Design and develop production-ready Generative AI and agentic AI applications.
- Build LLM-powered solutions using OpenAI, Anthropic, open-source models, Azure OpenAI, AWS Bedrock, or equivalent platforms.
- Develop RAG pipelines, prompt engineering workflows, vector search, and knowledge-based AI applications.
- Build and orchestrate AI agents using frameworks such as LangChain, LangGraph, LangFuse, LangSmith, or equivalent tools.
- Develop scalable cloud-native applications using 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 high-quality, maintainable software using strong OOP/OOD, DSA, testing, and code instrumentation practices.
- Collaborate on architecture and technical designs using business context, sequence, activity, state, entity relationship, and data-flow diagrams.
- Implement CI/CD, DevSecOps, SRE, security, and quality engineering practices.
- Use tools such as GitHub, Azure DevOps, SonarQube, MLflow, and related engineering platforms.
- Apply cost-aware engineering and FinOps principles to cloud and AI workloads.
Skills & Experience
- 6–9 years of overall software engineering experience.
- 3+ years of hands-on experience building AI/ML, Generative AI, and/or agentic applications.
- Strong programming experience in Python and SQL.
- Experience with one or more of C#/.NET, Java, NodeJS, Angular, or React.
- Strong 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.
- Knowledge of PyTorch/TensorFlow is desirable.
- Experience with MLflow, LangFuse, LangSmith, or equivalent AI observability/evaluation tools.
- Strong understanding of OOP/OOD, data structures, algorithms, system design, and software testing.
- Experience with DevSecOps, SRE, XP/Lean, GitHub/Azure DevOps, and SonarQube.
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