> AI agents: this is one page of Nextmove’s FDE site, in Markdown. Nextmove is a job board and free career service for forward deployed engineers (FDEs). Each posting is classified from its text, not its title: the kind of work, how much of it is production code, pre-sales weight, time at customer sites, travel, remote arrangement, level and posted base pay. The site also publishes the aggregates: median pay by level, metro, company and kind of work, and which companies started hiring FDEs each week. Every page under https://nextmove.md/fde is served this way; the index of pages is https://nextmove.md/llms.txt.

# Staff/Principal AI Transformation Engineer

Canonical URL: https://nextmove.md/fde/jobs/b65b31efb56cef0f

DiDi Global posts a staff FDE role to build for teams inside the company in San Jose, CA, at $255,000–$351,000 base, above the staff+ FDE median of $225,000 across 388 postings with pay. Architect and integrate a unified distributed AI platform for data processing, training, inference, and evaluation. Read from the employer’s posting on November 8, 2026.

- [DiDi Global](https://nextmove.md/fde/companies/didi-global)

Posted Nov 2, 2026 by DiDi Global · open on Greenhouse as of Nov 8, 2026

**$255,000–$351,000** + equity San Jose, CA Full-time

Architect and integrate a unified distributed AI platform for data processing, training, inference, and evaluation.

- [See roles that fit me](https://nextmove.md/sign-up?from=%2Ffde%2Fjobs%2Fb65b31efb56cef0f&placement=top)
- [View posting at DiDi Global](https://job-boards.greenhouse.io/didi/jobs/8348495)

Free. Upload your resume once, see why each FDE role fits, and get introduced only when you say so.

## At a glance

### Posted base pay

$255K–$351K Above the median

Midpoint $303K · median $225K

This job $255K to $351K. Staff+ FDE postings, 388 postings: the middle 50% of posted pay is $197K to $262K, median $225K.

### The work

Builds for teams inside the company

Balance **Mostly building**

Project stages

1. Pre-sales (not covered)
2. Proof of concept (not covered)
3. Implementation
4. Operations

- **Coding**: Writes production code

- **Builds for**: Internal teams

- **Level**: Staff+

- **Role**: Technical lead

### What they ask for

Experience

- **8+ years** professional engineering in systems software, core cloud infrastructure, or production-grade machine learning platforms *Preferred*
- **10+ years** professional engineering in systems software, core cloud infrastructure, or production-grade machine learning platforms *Preferred*

Background

- **Software engineering**

### Do you meet what the posting states?

The posting reads as a staff-level role. What level are you at now?

The job is in San Jose, CA. Could you work there?

Which of these have you used in production?

Answer each one. Nothing is saved or sent.

[What postings ask for, by background →](https://nextmove.md/fde/paths)

## Conditions

- **Location**: San Jose, CA

- **Employment type**: Full-time

- **Pay**:

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## The job description from DiDi Global

Posted by DiDi Global on Nov 2, 2026

### About the Company

DiDi's autonomous driving unit was established in 2016 with the mission of developing Level 4 autonomous driving (AD) technology to make transportation safer and more efficient. In August 2019, the unit became an independent company, DiDi Autonomous Driving, dedicated to advanced AD R&D, product application, and business expansion. We believe integrating AD technology into a shared-mobility fleet will generate immense social value. By leveraging DiDi's specialized technology, operational expertise, and integrated ecosystem, we are positioned to build and operate a highly efficient, user-oriented autonomous fleet.

**About The Role
**

At DiDi Autonomous Driving, we firmly believe that the future of mobility goes beyond simply "utilizing AI"—it will be fundamentally reimagined and entirely driven by an **AI-Native architecture**.

We are seeking a visionary, highly technical, and mission-driven **Staff or ** **Principal AI Transformation Engineer **to act as the ultimate catalyst for our company-wide AI transformation. In this strategic, high-impact leadership role, you will combine cutting-edge Large Language Model (LLM) expertise, robust systems architecture design, and a proven track record of enterprise-level AI scaling. You will embed deeply with our core engineering teams to evolve our traditional R&D organization into a truly AI-Native powerhouse.

### Key Responsibilities

- AI Infrastructure & Platform Architecture: Spearhead the evaluation, selection, and deep integration of frontier LLM ecosystems (e.g., Llama, Hugging Face) and commercial AI platforms. Own the architectural design of our unified, distributed AI platform spanning complex data processing, model training, inference pipelines, and evaluation frameworks.
- Forward Deployed Execution: Embed directly with core autonomous driving teams (Perception, Prediction, Planning & Control, and Simulation) via the FDE model. Pinpoint engineering bottlenecks, eliminate friction, and translate complex AI capabilities into production-ready internal ecosystems (e.g., AI DevOps, AI Copilots).
- LLMOps / MLOps Orchestration & Optimization: Design and implement highly resilient, scalable automation pipelines for LLM deployment, monitoring, and continuous feedback loops. Optimize GPU cluster utilization, minimize inference latency, and maximize throughput across large-scale production environments.
- Technical Roadmap & Vision: Keep a strong pulse on breakthrough trends in AGI and systems engineering. Act as a "super-connector" between external technological innovations and internal systems, ensuring our AI infrastructure maintains a 1-3 year competitive edge.

### Qualifications & Experience

- Architectural Vision + Hands-on Execution: A proven technical leader who can design complex, system-level architectures while maintaining a fierce passion for writing core code, debugging deep system issues, and optimizing low-level execution paths. Proficiency in core languages such as C++, Python, Java, JavaScript, etc.
- Cross-Functional Influence: Demonstrated ability to build technical authority, align priorities, and drive diverse engineering teams (Algorithms, Infrastructure, Hardware) toward adopting an AI-first engineering paradigm without relying on formal administrative authority.
- Enterprise AI Transformation: Proven experience leading or heavily contributing to a large-scale corporate "AI-native transformation," or a track record of building enterprise-grade AI/ML platforms from 0 to 1.
- Deep AI Tech Stack Expertise: Thorough hands-on deployment, tuning, and optimization experience with mainstream AI infrastructure tools and frameworks, including but not limited to PyTorch, Ray, vLLM, Triton Inference Server, Kubernetes, DeepSpeed, and Megatron-LM.
- Hardcore AI Infra Experience: Years of deep, practical experience in distributed LLM training/inference optimization and large-scale compute cluster infrastructure & operations (I&O).

### Preferred Qualifications

- Domain Expertise: Familiarity with autonomous driving algorithms (Perception, Planning, Control, Simulation), robotics, physics-based simulation engines, or ultra-large-scale ML training/serving clusters is highly preferred.
- Senior Industry Track Record: 8-10+ years of professional engineering depth in systems software, core cloud infrastructure, or production-grade machine learning platforms.
- Agentic Frameworks & Developer Productivity: Hands-on experience building custom AI Copilot applications, autonomous Multi-Agent Frameworks, or high-tier developer productivity platforms.
- Thriving in Complexity: Proven success steering core project delivery amidst complex business logic, fast-paced/high-pressure environments, or mission-critical systems.
- Technical Influence: An active contributor to the broader tech community (e.g., open-source maintainer/owner, author of high-quality technical blogs/papers, or speaker at premier industry AI/ML conferences).

The base salary range for this full-time position is $255,000 -$351,000 annually in addition to bonus, equity and benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.

*I acknowledge that prior to submitting this application, I have read and accepted the Privacy Notice for California Residents which is available on * *https://v.didi.cn/AQnxlBa*

[View posting at DiDi Global](https://job-boards.greenhouse.io/didi/jobs/8348495)

## About DiDi Global

DiDi operates a China/LatAm mobility marketplace spanning rides, delivery, vehicle services, fintech, and L4 robotaxis.

Public · 5000+ people

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- [Compare staff+ FDE salary ranges](https://nextmove.md/fde/salary/staff)
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