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Generative AI Engineer
Generative AI EngineerTuring • Panchkula, Haryana, India
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Generative AI Engineer

Generative AI Engineer

Turing • Panchkula, Haryana, India
19 days ago
Job description

About the role :

Turing is looking for people with LLM experience to join us in solving business problems for our Fortune 500 customers. You will be a key member of the Turing GenAI delivery organization and part of a GenAI project. You will be required to work with a team of other Turing engineers across different skill sets. In the past, the Turing GenAI delivery organization has implemented industry leading multi-agent LLM systems, RAG systems, and Open Source LLM deployments for major enterprises.

Required skills

  • 7+ years of professional experience in building Machine Learning models & systems
  • 1+ years of hands-on experience in how LLMs work & Generative AI (LLM) techniques particularly prompt engineering, RAG, and agents.
  • Expert proficiency in programming skills in Python, Langchain / Langgraph and SQL is a must.
  • Expert in architecting GenAI applications / systems using various frameworks & cloud services
  • Good proficiency in using various cloud services from Azure, GCP, or AWS for building the GenAI applications
  • Experience in driving the engineering team toward a technical roadmap.
  • Excellent communication skills to effectively collaborate with business SMEs

Roles & Responsibilities

  • Build the technical roadmap given a business requirement and own the delivery of the same
  • Lead the engineering team toward a technical roadmap and ensure timely execution of the roadmap to achieve customer satisfaction.
  • Develop and optimize LLM-based solutions : Lead the design, training, fine-tuning, and deployment of large language models, leveraging techniques like prompt engineering, retrieval-augmented generation (RAG), and agent-based architectures.
  • Codebase ownership : Maintain high-quality, efficient code in Python (using frameworks like LangChain / LangGraph) and SQL, focusing on reusable components, scalability, and performance best practices.
  • Cloud integration : Aide in deployment of GenAI applications on cloud platforms (Azure, GCP, or AWS), optimizing resource usage and ensuring robust CI / CD processes.
  • Cross-functional collaboration : Work closely with product owners, data scientists, and business SMEs to define project requirements, translate technical details, and deliver impactful AI products.
  • Mentoring and guidance : Provide technical leadership and knowledge-sharing to the engineering team, fostering best practices in machine learning and large language model development.
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