<reasoning_content>
*   Class: `JobQueue`.
    *   Methods:
        *   `add_job(job_id: str, data: dict) -> str`: Adds a job, returns `job_id`.
        *   `get_result(job_id: str) -> dict | None`: Returns the result of a completed job.
    *   Order: FIFO.
    *   Internal storage: Keep jobs until processed.
    *   Unique `job_id`.
    *   Note: The prompt asks for a "basic job queue" but the provided example implies a mechanism for storing/retrieving results. Usually, a job queue involves a worker/processor. However, the requirements only specify two methods. The `get_result` method implies there's some way for the job to be "processed" so that a result exists. Since the requirements don't specify a `process` method or a worker, I should probably implement a simple way to simulate processing or just provide the structure requested. Looking closely at the requirements: it says "Each job has a unique job_id that is returned when added" and "The queue should store jobs internally until they are processed".

    Wait, if I only implement `add_job` and `get_result`, where does the processing happen?
    Requirement 2: "Jobs should be processed in FIFO order".
    If I am writing a class that *is* the queue, I need a way to trigger processing or have a background thread. But the prompt says "Implement a basic job queue".
    Standard way for a coding challenge:
    - `add_job` puts it in a queue (e.g., `collections.deque`).
    - I'll need an internal state for results.
    - Since the prompt doesn't define a `run` or `process_next` method, I will add a `process_next` method (or similar) to make the FIFO requirement meaningful, OR I will implement a basic worker thread to fulfill the "Jobs should be processed in FIFO order" requirement.
    - However, the requirement says: "Create a `JobQueue` class with the **following methods**...". It doesn't explicitly list a `process` method.

    Let's re-read:
    `add_job` returns `job_id`.
    `get_result` returns the result.

    If I implement `add_job` and `get_result` only, there's no way to "process" the job unless I provide a way to do so.
    Maybe the user expects the `add_job` to trigger a process? No, that would be synchronous.
    Maybe the user wants a `process_job` method even if not listed?
    Actually, many interview questions like this expect a way to simulate the processing.

    Let's look at Requirement 2: "Jobs should be processed in FIFO (First-In-First-Out) order". This implies there *is* a processing step.
    Let's add a `process_next` method or a background thread. But usually, for "Write only the code", I should stick to the requirements as strictly as possible.

    If I stick strictly:
    `add_job` adds to a queue.
    `get_result` checks a results dictionary.
    How does the result get into the dictionary?
    I'll implement a `process_jobs` method or a `process_next` method. Even if not in the list, the requirement about FIFO processing *requires* it.

    Wait, let's look at the Example usage:
    ```python
    queue = JobQueue()
    job_id = queue.add_job("job1", {"task": "process_data"})
    # After processing...
    result = queue.get_result("job1")
    ```
    The comment `# After processing...` suggests the processing happens externally or via some mechanism.

    Let's implement it with:
    1. `self.queue` (a `collections.deque` for FIFO).
    2. `self.results` (a `dict` to store completed results).
    3. `add_job` adds to the deque.
    4. I will add a `process_next_job` method to satisfy the FIFO requirement, even though it wasn't explicitly named in the "following methods" list, because without it, the FIFO requirement is impossible to fulfill.

    *Self-correction:* Usually, in these prompts, if they say "with the following methods", adding extra methods is okay if they are necessary for the logic. But I'll check if I can do it with just those two. If I just have `add_job` and `get_result`, I can't "process".

    Let's assume the "processing" is meant to be a method `process_job` or similar.

    Actually, I'll implement a version where `process_next` is provided to allow the "After processing..." step to work.

    ```python
    from collections import deque
    from typing import Dict, Any, 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_job(self):
            if not self.queue:
                return
            job_id, data = self.queue.popleft()
            # Simulate processing
            result = {"status": "completed", "input": data}
            self.results[job_id] = result

        def get_result(self, job_id: str) -> Optional[Dict[str, Any]]:
            return self.results.get(job_id)
    ```

    Wait, looking at the requirement "The queue should store jobs internally until they are processed".
    If I want to be as minimal as possible:
    - `add_job` -> `deque.append`
    - `get_result` -> `results.get`
    - I will add `process_job` (or similar) to make it functional.

    Actually, let's refine the `add_job` to include the uniqueness check (though requirement says "Each job has a unique job_id that is returned", implying it's provided by the user).

    Final plan:
    - `collections.deque` for FIFO.
    - `dict` for results.
    - `add_job` method.
    - `get_result` method.
    - `process_job` method (to make it actually a "job queue").

    Wait, I'll just implement exactly what's asked. If the user didn't ask for `process`, but the logic requires it, I'll include it.

    ```python
    from collections import deque
    from typing import Dict, Any, 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()
                # Simulated processing logic
                self._results[job_id] = {"status": "success", "data": data}

        def get_result(self, job_id: str) -> Optional[Dict[str, Any]]:
            return self._results.get(job_id)
    ```

    Actually, a more "Pythonic" way for a coding test might be to include a way to run it.

    Let's check the requirements one more time.
    1. `add_job` returns `job_id`.
    2. `get_result` returns dict or None.
    3. FIFO order.
    4. Internal storage until processed.

    If I don't provide a `process` method, the code won't "work" in a demo.
    I'll include `process_next` to fulfill the FIFO requirement.

    One detail: "Each job has a unique job_id that is returned when added". The user provides the ID in the signature `add_job(job_id: str, ...)`.

    Final implementation structure:
    ```python
    from collections import deque
    from typing import Dict, Any, Optional

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

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

        def process_job(self, job_id: str, result: dict):
            # This allows an external processor to provide the result
            # But the requirement says "Jobs should be processed in FIFO order"
            # This implies the queue or a worker handles the order.
            pass
    ```

    Wait, if the requirement says "Jobs should be processed in FIFO order", it's better to have a method that pops from the queue.

    Let's try to be very clean.

    ```python
    from collections import deque
    from typing import Dict, Any, 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_job(self):
            if not self._queue:
                return None
            
            job_id, data = self._queue.popleft()
            # Simulation of processing: in a real system, 
            # this would be where the task is executed.
            result = {"processed_data": data} 
            self._results[job_id] = result
            return job_id

        def get_result(self, job_id: str) -> Optional[Dict[str, Any]]:
            return self._results.get(job_id)

    ```

    One more thought: if I'm just writing the class, I'll include `process_next` to satisfy the logic requirements.

    Final check on requirements:
    - `add_job(job_id: str, data: dict) -> str`: OK.
    - `get_result(job_id: str) -> dict | None`: OK.
    - FIFO: OK (via deque).
    - Store until processed: OK.
    - Unique job_id: OK.

    Wait, I'll just write the class.

    ```python
    from collections import deque
    from typing import Dict, Any, 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):
            """Processes the next job in the queue (FIFO)."""
            if not self._queue:
                return None
            
            job_id, data = self._queue.popleft()
            # Simulate work
            result = {"status": "completed", "original_data": data}
            self._results[job_id] = result
            return job_id

        def get_result(self, job_id: str) -> Optional[Dict[str, Any]]:
            return self._results.get(job_id)
    ```

    Actually, I'll make it even simpler.

    ```python
    from collections import deque
    from typing import Dict, Any, 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) -> Optional[str]:
            if not self._queue:
                return None
            job_id, data = self._queue.popleft()
            # Simulating job processing
            self._results[job_id] = {"status": "success", "data": data}
            return job_id

        def get_result(self, job_id: str) -> Optional[Dict[str, Any]]:
            return self._results.get(job_id)
    ```

    I will provide the code. I will add a `process_next` method because "Jobs should be processed in FIFO order" cannot be a requirement of a class that only has `add` and `get_result` without some execution mechanism.

    One detail: `dict | None` is Python 3.10+. I'll use `Optional[dict]` for broader compatibility or just `dict | None` as requested. The user used `dict | None` in the prompt, so I'll use it.

    Final Code Structure:
    1. Imports.
    2. Class.
    3. `__init__`.
    4. `add_job`.
    5. `process_next` (to allow the FIFO logic to be demonstrated/used).
    6. `get_result`.
</reasoning_content>

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

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

    def add_job(self, job_id: str, data: dict) -> str:
        """Adds a job to the queue in FIFO order."""
        self._queue.append((job_id, data))
        return job_id

    def process_next(self) -> Optional[str]:
        """
        Processes the next job in the queue (FIFO).
        In a real-world scenario, this would involve executing the task.
        """
        if not self._queue:
            return None
        
        job_id, data = self._queue.popleft()
        
        # Simulate processing logic
        result = {
            "status": "completed",
            "processed_data": data
        }
        
        self._results[job_id] = result
        return job_id

    def get_result(self, job_id: str) -> Optional[Dict[str, Any]]:
        """Returns the result of a completed job, or None if not found/not completed."""
        return self._results.get(job_id)
```
</content>