Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises looking to deploy advanced AI systems. Turing accelerates frontier research with high-quality data, specialized talent, and training pipelines that advance thinking, reasoning, coding, multimodality, and STEM. For enterprises, Turing builds proprietary intelligence systems that integrate AI into mission-critical workflows, unlock transformative outcomes, and drive lasting competitive advantage.
Recognized by Forbes, The Information, and Fast Company among the world’s top innovators, Turing’s leadership team includes AI technologists from Meta, Google, Microsoft, Apple, Amazon, McKinsey, Bain, Stanford, Caltech, and MIT. Learn more at www.turing.com
Overview
Turing is looking for people with GenAI experience to join us in solving business problems for our Fortune 500 customers. You will be a key member of the Turing Intelligence delivery organization and part of a GenAI project. You will be required to lead 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 and LLM deployments for major enterprises.
ResponsibilitiesSolutioning & Lead
- 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.
- Design robust multi-agent architectures including supervisor-router patterns with dynamic sub-agent routing and stopping conditions.
- Mentoring and guidance: Provide technical leadership and knowledge-sharing to the engineering team, fostering best practices in machine learning and large language model development.
Hands-on Skills
- Develop LLM-based solutions: Lead the design, training, fine-tuning, and deployment of large language models, leveraging techniques like retrieval-augmented generation (RAG) and multi-agent based architectures.
- Build and maintain agent evaluation pipelines, including offline eval datasets, LLM-as-judge, and CI-integrated eval runs.
- Codebase ownership: Build & 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: 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.
- 12+ years of professional experience in software engineering and building applications/systems.
- 2+ years of hands-on experience in how LLMs work & Generative AI (LLM) techniques, particularly multi-agent systems.
- Expert proficiency in Python, Langgraph, and SQL.
- Expert in architecting GenAI applications/systems using various frameworks & cloud services.
- Expert proficiency in using AI tools like Claude Code, Codex, Cursor, Windsurf, and the likes.
- Expert proficiency in AI observability & evaluation tools like Langsmith, Langfuse, or similar.
- Good proficiency in using various cloud services from Azure, GCP, or AWS for building GenAI applications.
- Experience in driving the engineering team toward a technical roadmap.
- Excellent communication skills to effectively collaborate with business SMEs.
We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value.
We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection
We are AI forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity.
Amazing work culture (Super collaborative & supportive work environment; 5 days a week)
Awesome colleagues (Surround yourself with top talent from Meta, Google, LinkedIn etc. as well as people with deep startup experience)
Competitive compensation
Flexible working hours
Don’t meet every single requirement? Studies have shown that women and people of color are less likely to apply to jobs unless they meet every single qualification. Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace and celebrate authenticity, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles.
For applicants from the European Union, please review Turing's GDPR notice here.
Skills Required
- 12+ years of professional software engineering experience
- 2+ years hands-on experience with LLMs and Generative AI techniques, particularly multi-agent systems
- Expert proficiency in Python
- Expert proficiency in LangGraph
- Expert proficiency in SQL
- Experience architecting GenAI applications and systems
- Experience designing multi-agent architectures (supervisor-router patterns, dynamic routing, stopping conditions)
- Experience with retrieval-augmented generation (RAG), training, fine-tuning and deploying LLMs
- Experience building agent evaluation pipelines (offline eval datasets, LLM-as-judge, CI-integrated eval runs)
- Familiarity with LangChain
- Proficiency with AI tools such as Claude Code, Codex, Cursor, Windsurf
- Proficiency with AI observability and evaluation tools like Langsmith or Langfuse
- Cloud deployment experience on Azure, GCP, or AWS and building CI/CD for GenAI apps
- Experience driving engineering teams toward a technical roadmap and mentoring engineers
- Excellent communication skills to collaborate with product owners, data scientists, and business SMEs
Turing Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Turing and has not been reviewed or approved by Turing.
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Fair & Transparent Compensation — Feedback suggests USD-denominated pay and access to higher-paying clients can outpace local benchmarks for many non‑U.S. developers. Payout timing and processing are described as predictable once engagements begin, which supports confidence in earnings.
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Wellbeing & Lifestyle Benefits — Feedback suggests remote‑first work with flexible hours is a consistent positive that enhances day‑to‑day balance. The ability to work from anywhere and maintain autonomy is frequently highlighted as part of the overall rewards experience.
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Healthcare Strength — Feedback suggests some U.S. corporate roles include comprehensive health benefits, with individual accounts referencing employer‑covered medical insurance. These signals indicate stronger healthcare support for certain employee populations.
Turing Insights
What We Do
We now live in a remote-first world and every company is in a race to find the best remote engineers. There are so many amazing engineers all over the world. Turing’s mission is to help unleash the world’s untapped human potential. More than 300 companies, including those backed by Google Ventures, Bloomberg, Andreessen, Founders Fund, and Kleiner are already using Turing to spin up their engineering dream teams. Turing’s hiring platform combines the planetary reach and AI to deliver your ideal engineers in order to help you spin up your engineering dream team. Our deep matching intelligence finds the best Turing developers across 100+ skills like React, Node, Python, Golang, Angular, Swift, Java, and many more. As part of our rigorous vetting process, we also review software engineers’ technical abilities, English skills, and remote working capabilities. Turing ensures time zone overlap, transparency, and reliable communication in order to make remote development easy for you after the match. The Turing team has deep expertise in AI and building engineering dream teams in the U.S. at top companies. Turing company is backed by well-known investors like Facebook’s initial CTO (Adam D’Angelo), executives from Google, Facebook, Amazon, Twitter, Founders Fund (investors in Facebook, Tesla, Asana, etc). Turing.com is led by serial A.I. entrepreneurs Jonathan Siddharth and Vijay Krishnan, their last A.I. firm leveraged remote talent and had a successful acquisition.
