Turing
About this role
Forward deployed engineering means building directly against a customer's problem rather than a roadmap, and Turing does that for enterprises deploying advanced AI plus frontier AI labs needing research pipelines. This role leads the design, training, fine tuning and deployment of large language model solutions, using prompt engineering, retrieval augmented generation and agent based architectures. It is genuinely hands on: the posting asks for expert Python with LangChain or LangGraph and SQL as a must, and for high quality, reusable, scalable code that you maintain. You also work with product owners, data scientists and business subject matter experts to define requirements and translate the technical detail. It sits in our customer facing group because the work is done alongside customers, but the requirement list is an engineering one throughout.
Who this is for
Required by the posting: 8 or more years of professional experience building machine learning models and systems. 1 or more years of hands on experience with how LLMs work and with generative AI techniques, specifically prompt engineering, RAG and agents. Expert proficiency in Python, LangChain or LangGraph, and SQL, which the posting states is a must. Experience driving an engineering team toward a technical roadmap.
The day to day: lead the design, training, fine tuning and deployment of large language models, using prompt engineering, retrieval augmented generation and agent based architectures. Maintain high quality, efficient code in Python, with LangChain and LangGraph named, and SQL, focusing on reusable components, scalability and performance. Work closely with product owners, data scientists and business subject matter experts to define project requirements, translate technical detail and deliver AI products.
Note on the roadmap line: driving an engineering team toward a technical roadmap here reads as technical leadership rather than line management, since no hiring, performance or reporting responsibility appears anywhere in the posting.
Location: Bengaluru. Turing itself is based in San Francisco. Office days are not stated on this posting.
Who should apply: ML engineers eight or more years in who have shipped LLM systems into production and are comfortable working in front of a customer. Turing also lists a Principal Forward Deployed AI Engineer at 8 or more years with 4 to 6 of that in AI and ML specifically, so if you are further along, look at that one too.
The day to day: lead the design, training, fine tuning and deployment of large language models, using prompt engineering, retrieval augmented generation and agent based architectures. Maintain high quality, efficient code in Python, with LangChain and LangGraph named, and SQL, focusing on reusable components, scalability and performance. Work closely with product owners, data scientists and business subject matter experts to define project requirements, translate technical detail and deliver AI products.
Note on the roadmap line: driving an engineering team toward a technical roadmap here reads as technical leadership rather than line management, since no hiring, performance or reporting responsibility appears anywhere in the posting.
Location: Bengaluru. Turing itself is based in San Francisco. Office days are not stated on this posting.
Who should apply: ML engineers eight or more years in who have shipped LLM systems into production and are comfortable working in front of a customer. Turing also lists a Principal Forward Deployed AI Engineer at 8 or more years with 4 to 6 of that in AI and ML specifically, so if you are further along, look at that one too.
Apply on company site
Opens job-boards.greenhouse.io, the employer's own application page. Applying is always free.