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
The Role
We are looking for an elite engineer who builds like a hacker and communicates like a consultant. You will not just be building models in a notebook; you will be deployed to the front lines to build, architect, and ship end-to-end Agentic AI products directly for our most strategic customers.
This is a high-stakes role. You will face "tricky" customers who have vague requirements and high expectations. Your job is to translate their chaos into technical order, write production-grade code, and deploy autonomous agents that solve their actual business problems.
What You Will Do
- Build & Deploy (60%):
Design and ship full-stack AI applications. You own the pipeline from data ingestion to the LLM inference layer to the frontend interface.
Architect autonomous agentic workflows (using frameworks like LangChain, LangGraph, or custom implementations) that can reason, plan, and execute complex tasks.
Write robust, clean, and highly testable code (Python/Typescript). "It works on my machine" is not acceptable; it must work in the customer's restricted cloud environment.
Handle DevOps and MLOps constraints: Dockerizing agents, managing Kubernetes clusters, and optimizing inference latency.
- Customer Engineering (40%):
Serve as the technical face of the company for our most demanding accounts.
Navigate complex stakeholder environments. You will push back on unrealistic demands, clarify ambiguous requirements, and steer "tricky" customers toward technically feasible solutions without breaking rapport.
Translate technical constraints into business value for non-technical executives.
Generate high-quality data for our customers and ability to review the data generated by other experts. This is one of the most critical aspects of the role.
The "Must-Haves"
- Experience: 8–12 years of total engineering experience. You started as a strong Software Engineer and evolved into an AI specialist.
- Education: B.S./M.S. in Computer Science, Math, or Physics from a top-tier institution (IIT, MIT, Stanford, Harvard, Berkeley, CMU, or similar global top-ranking universities).
- Deep AI Fluency: You aren't just calling APIs. You understand RAG implementation nuances, vector database optimization, fine-tuning (LoRA/PEFT), and the architecture of agentic loops.
- Production Engineering: Experience with end-to-end deployment (AWS/GCP/Azure, CI/CD pipelines, Terraform, Docker).
The "Why You" (Soft Skills)
- Thick Skin & High EQ: You don't get flustered when a customer changes their mind for the third time in a week. You can hold your ground with a CTO and explain "why not" to a CEO.
- Extreme Attention to Detail: You catch the edge cases that others miss. You obsess over error handling, retry logic in agents, and data privacy.
- Grit: You enjoy the "messy" work of integrating legacy enterprise data just as much as prompting the latest model.
What will set you apart
- Public Code: A visible GitHub footprint is very helpful. We want to see your side projects, your contributions to open source, or your experiments with LLMs. Please include your GitHub link in your application.
Tech Stack
- Languages: Python (Expert).
- AI/Data (Expertise in all is not required): PyTorch, LangChain, LlamaIndex, Pinecone/Weaviate, OpenAI/Anthropic APIs, HuggingFace.
- Infra (Expertise in all is not required): Kubernetes, Terraform, AWS/GCP.
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
- 8-12 years of total engineering experience
- B.S./M.S. in Computer Science, Math, or Physics from a top-tier institution
- Deep understanding of RAG implementation nuances and vector database optimization
- Experience with end-to-end deployment on cloud platforms and CI/CD pipelines
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.
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