<p><p><b style="background-color: inherit;">About the role :</b><br/><br/>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.<br/><br/><b style="background-color: inherit;">Required skills :</b><br/><br/>- 12+ years of professional experience in building Machine Learning models & systems<br/><br/></p><p>- 1+ years of hands-on experience in how LLMs work & Generative AI (LLM) techniques particularly prompt engineering, RAG, and agents.<br/><br/></p><p>- Expert proficiency in programming skills in Python, Langchain/Langgraph and SQL is a must.<br/><br/></p><p>- Expert in architecting GenAI applications/systems using various frameworks & cloud services<br/><br/></p><p>- Good proficiency in using various cloud services from Azure, GCP, or AWS for building the GenAI applications<br/><br/></p><p>- Experience in driving the engineering team toward a technical roadmap.<br/><br/></p><p>- Excellent communication skills to effectively collaborate with business SMEs<br/><b style="background-color: inherit;"><br/></b></p><p><p><b style="background-color: inherit;">Roles & Responsibilities :</b></p><p><br/>- Build the technical roadmap given a business requirement and own the delivery of the same.</p><br/></p><p>- Lead the engineering team toward a technical roadmap and ensure timely execution of the roadmap to achieve customer satisfaction.<br/><br/></p><p>- 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.<br/><br/></p><p>- 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.<br/><br/></p><p>- Cloud integration: Aide in deployment of GenAI applications on cloud platforms (Azure, GCP, or AWS), optimizing resource usage and ensuring robust CI/CD processes.<br/><br/></p><p>- 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.<br/><br/></p><p>- Mentoring and guidance: Provide technical leadership and knowledge-sharing to the engineering team, fostering best practices in machine learning and large language model development.</p><br/></p> (ref:hirist.tech)