Q
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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