<reasoning_content>
*   Goal: Implement a `JobQueue` class in Python.
    *   Requirements:
        *   `add_job(job_id: str, data: dict) -> str`: Adds a job, returns ID.
        *   `get_result(job_id: str) -> dict | None`: Returns result or None.
        *   FIFO order (implies a queue structure).
        *   Storage: Jobs must stay in queue until processed.
        *   Uniqueness: Each job has a unique ID.
    *   Constraints: Python code only, no explanations.

    *   Need a way to store jobs: `collections.deque` is ideal for FIFO.
    *   Need a way to store results: A dictionary `results = {}`.
    *   Need to handle the "processing" aspect. Since the prompt says "After processing...", but doesn't explicitly ask for a `process_jobs()` method, I should probably include a simple way to trigger processing or simulate it to make the example valid.
    *   Wait, the prompt says "Jobs should be processed in FIFO order". This implies a consumer logic.
    *   Let's look at the signature again: `add_job` returns `job_id`. `get_result` returns the dict.
    *   How is a job "processed"? Usually, in these coding prompts, if a `process` method isn't specified, I should provide a way to process the queue (e.g., `process_all()` or similar) so that `get_result` actually returns something. Or, maybe the prompt assumes the user calls a process method internally.
    *   Actually, let's look at the requirement "The queue should store jobs internally until they are processed".
    *   I'll implement a `process_jobs()` method to make it functional, even if not explicitly listed in the signature requirements (the requirements list methods `add_job` and `get_result`, but "processed in FIFO" implies a process step).
    *   Wait, if I don't have a process method, how does the user actually "process" it?
    *   Maybe I should implement a simple worker or a method to process the next job.
    *   Let's look at the example:
        ```python
        job_id = queue.add_job("job1", {"task": "process_data"})
        # After processing...
        result = queue.get_result("job1")
        ```
        This implies there's an implicit "processing" step. I'll add a `process_next()` or `process_all()` method to allow the user to move jobs from the queue to the results.

    *   *Revised plan:*
        1. Use `collections.deque` for the queue of `(job_id, data)`.
        2. Use a dictionary `self.results` to store outcomes.
        3. `add_job` appends to the deque.
        4. `process_next` (I'll add this to satisfy the FIFO requirement) pops from left and puts into `results`.
        5. `get_result` checks the dictionary.

    *   *Wait*, the prompt says: "Create a JobQueue class with the following methods: ...". It only lists two methods. If I add a third, it's fine, but I must ensure the two required ones work correctly.
    *   However, if there is no way to "process", `get_result` will always be `None`.
    *   Maybe the prompt implies that `add_job` puts it in a list, and I should have a way to process it.
    *   Let's provide a simple `process_all` or `process_next` method so the code is actually usable.

    *   *Refined Implementation:*
        *   `self.queue = deque()`
        *   `self.results = {}`
        *   `add_job(job_id, data)`: `self.queue.append((job_id, data)))`, return `job_id`.
        *   `process_jobs()` (optional but helpful): Pops from `self.queue`, calculates a result (e.g., just echoes the data), puts in `self.results`.
        *   `get_result(job_id)`: returns `self.results.get(job_id)`.

    Actually, looking at the prompt "Jobs should be processed in FIFO order", I should probably make sure that the `process` logic happens. Since the prompt doesn't specify the processing logic, I'll assume "processing" just means moving it from the queue to the results dictionary.

    Let's write the code.

    ```python
    from collections import deque
    from typing import Dict, Optional

    class JobQueue:
        def __init__(self):
            self.queue = deque()
            self.results = {}

        def add_job(self, job_id: str, data: dict) -> str:
            self.queue.append((job_id, data))
            return job_id

        def process_jobs(self):
            while self.queue:
                job_id, data = self.queue.popleft()
                # Simulate processing logic
                self.results[job_id] = {"status": "completed", "data": data}

        def get_result(self, job_id: str) -> dict | None:
            return self.results.get(job_id)
    ```

    Actually, looking at the prompt again, it says "Create a JobQueue class with the following methods" and lists only two. I will provide only those two plus a `process_jobs` (or similar) to make the example work, or I'll just implement the two and assume the user knows they need to trigger some logic. But "processed in FIFO order" is a requirement. If I don't have a process method, it's not being processed.

    I'll include a `process_next_job` method to make the logic complete.

    Wait, the prompt says "Write only the Python code, no explanations." I should stick to the requested signature and make it functional.

    Actually, a common pattern for these "Job Queue" prompts is that the "processing" is something the user does via a separate thread or method. I'll add a `process_next_job` method.

    Let's refine:
    - `add_job`: append to deque.
    - `process_next_job`: pop from deque, "process" (e.g. simple transform), store in dict.
    - `get_result`: fetch from dict.

    Wait, maybe the prompt wants me to handle the processing inside a method? No, it says "After processing...". This implies the processing is a discrete step.

    I'll provide `add_job`, `process_jobs` (to satisfy FIFO requirement), and `get_result`.

    Wait, I'll stick strictly to the requested methods but I'll make sure the internal logic supports FIFO.

    Actually, looking at the text "The queue should store jobs internally until they are processed", it means the class stores them.

    Let's try to make it as simple as possible.

    ```python
    from collections import deque
    from typing import Dict, Optional

    class JobQueue:
        def __init__(self):
            self.queue = deque()
            self.results = {}

        def add_job(self, job_id: str, data: dict) -> str:
            self.queue.append((job_id, data))
            return job_id

        def process_jobs(self):
            while self.queue:
                job_id, data = self.queue.popleft()
                # Example processing logic
                self.results[job_id] = {"result": data, "status": "success"}

        def get_result(self, job_id: str) -> dict | None:
            return self.results.get(job_id)
    ```

    I will check if I should include `process_jobs`. The prompt doesn't ask for it in the "methods" list, but "Jobs should be processed in FIFO order" is a requirement. I'll include it to ensure the logic is complete.

    Actually, I'll just include the two requested methods and a simple `process_all` method to ensure the FIFO requirement is observable.

    Wait, I'll just provide the class with the two methods and a `process_next` method so the example provided in the prompt actually works.

    Actually, let's look at the prompt's example:
    `job_id = queue.add_job("job1", {"task": "process_data"})`
    `# After processing...`
    `result = queue.get_result("job1")`

    This implies that the user might be calling `process_jobs()` or some internal mechanism is moving it. Since I'm writing the class, I'll include a `process_next` method.

    Wait, maybe I should just implement `process_next` and not worry if it wasn't in the list, because the requirements (FIFO, storage) are impossible to fulfill without a processing step.

    Actually, I'll keep it simple.

    ```python
    from collections import deque
    from typing import Dict, Optional

    class JobQueue:
        def __init__(self):
            self._queue = deque()
            self._results = {}

        def add_job(self, job_id: str, data: dict) -> str:
            self._queue.append((job_id, data))
            return job_id

        def process_next(self):
            if self._queue:
                job_id, data = self._queue.popleft()
                # Simulating processing logic
                self._results[job_id] = {"status": "completed", "data": data}

        def get_result(self, job_id: str) -> dict | None:
            return self._results.get(job_id)
    ```

    I'll omit the `process_next` from the "Requirements" list but include it so the code is functional. Or better, I'll just provide the requested two and a `process_all` method.

    Wait, if the user wants *only* those methods, I should probably just provide those and assume `process_jobs` is handled by the user somehow? No, that's impossible.

    I will provide the two requested methods and a `process_jobs` method to satisfy the "FIFO" and "processed" requirements.

    One more thought: Is it possible `add_job` should automatically process? No, "The queue should store jobs internally until they are processed". This clearly implies a state where they are in the queue but not yet processed.

    Let's provide the code.
</reasoning_content>

<content>
```python
from collections import deque
from typing import Dict, Optional

class JobQueue:
    def __init__(self):
        # FIFO queue to store jobs as (job_id, data) tuples
        self._queue: deque[tuple[str, dict]] = deque()
        # Dictionary to store results keyed by job_id
        self._results: Dict[str, dict] = {}

    def add_job(self, job_id: str, data: dict) -> str:
        """Add a job to the queue and return the job_id."""
        self._queue.append((job_id, data))
        return job_id

    def process_jobs(self):
        """
        Processes all jobs in the queue in FIFO order.
        This method is provided to satisfy the requirement that 
        jobs are processed and moved from the internal queue to results.
        """
        while self._queue:
            job_id, data = self._queue.popleft()
            # Simulate processing logic (e.g., transformation or computation)
            self._results[job_id] = {
                "status": "completed",
                "input_data": data,
                "output": f"Processed: {data.get('task', 'no_task')}"
            }

    def get_result(self, job_id: str) -> dict | None:
        """Retrieve the result of a completed job by its ID."""
        return self._results.get(job_id)

# Example Usage:
if __name__ == "__main__":
    queue = JobQueue()
    job_id = queue.add_job("job1", {"task": "process_data"})
    
    # Simulate the processing step
    queue.process_jobs()
    
    result = queue.get_result("job1")
    print(result)
```
</content>