Python Generative AI Engineer

Anlage Infotech; Hyderabad, Bengaluru; Hybrid; INR 3,000,000 - 4,200,000; Full time

Benefits offered by this job

Hybrid work model

Multiple locations

Job summary

Anlage Infotech invites a seasoned Applied AI engineer to Hyderabad/Bangalore/Gurugram. The role focuses on Python, SQL, Azure/AWS and GenAI with 6–9 years of experience in AI/ML and agentic applications.

You'll build AI/ML solutions, integrate LLMs, manage RAG pipelines, and work in a hybrid model (3 days in office, 2 days remote) across cloud-native stacks and modern DevOps practices.

Qualifications

• Bachelor's degree in computer science or related field.
• 5+ years experience with AI/ML tech: Angular, React, NodeJS, Python, .NET, Java, SQL/NoSQL, PyTorch, TensorFlow, LangChain/ LangGraph.
• 3+ years building AI/ML and GenAI apps, with LLM integration, RAG pipelines, prompts, vector databases, AI agent orchestration.

Skills

Python

SQL/NoSQL

Azure/AWS/GCP

GenAI

LLM integration

Cloud-native

DevOps tooling

LangChain/LangSmith

Education

Bachelor's degree in CS/SE/Data Science

Tools

Azure OpenAI

AWS Bedrock

Vertex AI

MLflow

LangFuse

LangSmith

Job description

Skill : Applied AI - Python+SQL+Azure/AWS+GenAI

Experience : 6-9 Yrs

Work location: Hyderabad/Bangalore/Gurugram

Work Model-Hybrid (3 days work from office / 2 days work from home )

Required Qualifications:

• A bachelors degree in computer science, software engineering, data science, machine learning, or related discipline. Experience is the most relevant factor.
• 5+ years of experience with most of the following: Angular, React, NodeJS, Python, C#, .NET, Java, SQL/NoSQL, PyTorch, TensorFlow, LangChain, LangGraph, as well as unit testing frameworks.
• 3+ years of experience building AI/ML and agentic applications, with hands-on GenAI experience across LLM integration (OpenAI, Anthropic, or open-source models), RAG pipelines, prompt engineering, vector databases, evaluations, and AI agent orchestration.
• 3+ years of experience with cloud-native engineering, using FaaS, PaaS, or micro-services on any of the cloud hyperscalers such as Azure, AWS, or GCP, including their AI/ML services such as Azure OpenAI, AWS Bedrock, or Vertex AI, plus application-level infrastructure-as-code and cost-aware engineering (FinOps accountability).
• Prior experience using methodologies & tools such as XP, Lean, DevSecOps, SRE, ADO, GitHub, SonarQube, MLflow, and agentic AI frameworks (e.g. LangFuse, LangSmith, or equivalent multi-agent orchestration tools) etc. to deliver high-quality products rapidly.