To fix the concurrency bug, we need to ensure that access to the shared dictionaries (`self.jobs` and `self.results`) is thread-safe. The race condition occurs because multiple threads can read, modify, and write to these dictionaries simultaneously without synchronization.

The fix involves using a `threading.Lock` to protect the critical sections of the code. Specifically, we need to ensure that the check for a job's existence, the retrieval of data, the processing, the storage of the result, and the deletion of the job happen atomically (or at least that the dictionary accesses are protected).

Here is the complete fixed implementation:

```python
import threading

class JobQueue:
    def __init__(self):
        self.jobs = {}
        self.results = {}
        # Initialize a lock to synchronize access to shared state
        self.lock = threading.Lock()

    def add_job(self, job_id, data):
        # Protect adding jobs to the queue
        with self.lock:
            self.jobs[job_id] = data
            return job_id

    def process_job(self, job_id, processor):
        # Protect the entire processing sequence.
        # This ensures that no other thread can interfere with the job's lifecycle
        # (checking existence, processing, writing result, deleting job).
        with self.lock:
            if job_id not in self.jobs:
                return False

            data = self.jobs[job_id]
            
            # Note: In a high-performance production system, you might want to 
            # release the lock while the processor runs to allow other threads 
            # to work. However, to strictly fix the race condition in this 
            # specific snippet while preserving the original logic (deleting the 
            # job only after processing), we keep the lock held. 
            # Alternatively, one could 'pop' the job inside the lock, process 
            # outside, and then write the result inside a lock, but that changes 
            # the error-handling behavior (job loss on failure).
            
            result = processor(data)

            # Fixed: Protected write to results to prevent race condition
            self.results[job_id] = result

            del self.jobs[job_id]
            return True

    def get_result(self, job_id):
        # Protect reading results
        with self.lock:
            return self.results.get(job_id)
```

### Explanation of Changes:
1.  **Added `self.lock`**: A `threading.Lock` instance is created in `__init__` to manage thread synchronization.
2.  **Locked `add_job`**: Ensures that adding a job to `self.jobs` is atomic, preventing race conditions if multiple threads try to add jobs simultaneously.
3.  **Locked `process_job`**: The entire method is wrapped in `with self.lock`. This serializes access to the shared state. It ensures that:
    *   Only one thread checks if a job exists at a time.
    *   Only one thread retrieves data for a specific job ID.
    *   The write to `self.results` happens safely without concurrent writes from other threads (fixing the specific bug mentioned).
    *   The deletion of the job from `self.jobs` happens safely.
4.  **Locked `get_result`**: Ensures that reading the results dictionary is thread-safe.

*Note: While holding the lock during `processor(data)` is the safest way to fix the bug while maintaining the original code's logic (where the job is deleted only after successful processing), in a high-concurrency environment, it is often better to `pop` the job from the queue inside the lock, process it outside the lock, and then write the result inside a lock. However, the solution above is the most direct fix that preserves the original behavior.*