Key skills
Generative AI applicationsAI/ML model deploymentCloud services proficiencyPython programmingLangchain/LanggraphSQL programmingTechnical leadershipcommunicationCollaboration skillsMentoringPythonSQLAIMachine LearningMLGenerative AIGenAILLMLarge Language ModelsLangChainLangGraphAWSAzureGCPCI/CDLeadershipCommunicationCollaboration
About this role
Turing is the world’s leading research accelerator for frontier AI labs, seeking to solve business problems for Fortune 500 customers. The role involves leading the engineering team in developing and deploying AI/ML models and systems, specifically focusing on Generative AI applications.
Responsibilities:
- Build the technical road map 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
- Continuous innovation: Stay abreast of the latest advancements in LLM research and generative AI, proposing and experimenting with emerging techniques to drive ongoing improvements in model performance
Requirements:
- 10–12+ years of professional, hands-on engineering experience, including 4–6+ years specializing in building and deploying AI/ML models and systems
- 1+ years of experience in developing Generative AI (LLM) applications using techniques like prompt engineering, RAG, and/or agents
- 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
- Expert proficiency in programming skills in Python, Langchain/Langgraph and SQL is a must
- Experience in driving the engineering team toward a technical roadmap
- Excellent communication skills to effectively collaborate with business SMEs