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AI Engineer - 6 - 12 Years

Exclusive opportunity

Onsite

AI Engineer - 6 - 12 Years

Quess

AI Engineer - 6 - 12 Years

Skills

PythonMicroservicesAIAzure

2 months ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Onsite

Published on:

31 August 2026

What they need


AI Engineer

Experience

  • 4 to 12 years of software engineering experience with hands-on experience in AI/GenAI application development
  • Experience building and deploying AI-enabled products, platforms, or enterprise solutions
  • Strong software engineering fundamentals with experience across backend systems, APIs, and cloud-native applications
  • Experience leading small teams or driving delivery across multiple engineers/workstreams
  • Comfortable working with Product, Engineering, and Architecture stakeholders

GenAI & Agentic Development

  • Design and build GenAI applications using frameworks such as LangChain, Semantic Kernel, LlamaIndex, or similar
  • Develop RAG-based solutions including ingestion, retrieval, orchestration, and response generation
  • Build agentic workflows involving tool usage, memory, and multi-step task execution
  • Integrate LLMs and AI services into enterprise applications and business processes
  • Drive adoption of AI-native engineering practices within the team

Technical Skills

  • Strong programming skills in Python and modern software engineering frameworks
  • Experience with LLM platforms such as Azure OpenAI, OpenAI, Anthropic, or equivalent
  • Experience building APIs, microservices, and cloud-native applications
  • Familiarity with vector databases, retrieval systems, and prompt engineering techniques
  • Working knowledge of CI/CD, containers, and cloud deployment practices

Delivery & Team Leadership

  • Lead delivery of AI engineering workstreams and key product features
  • Mentor and guide engineers on solution design, coding practices, and AI adoption
  • Partner with Product and Engineering leaders to translate business requirements into scalable AI solutions
  • Drive engineering quality, delivery predictability, and operational excellence

AI Engineering Practices

  • Define and promote best practices around prompt design, model evaluation, and AI application development
  • Leverage AI tools to improve engineering productivity and speed of delivery
  • Stay current with emerging AI technologies and identify opportunities to apply them within products

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