<reasoning_content>
*   Goal: Implement a `JobQueue` class in Python.
    *   Methods required:
        *   `add_job(job_id: str, data: dict) -> str`: Adds a job, returns ID.
        *   `get_result(job_id: str) -> dict | None`: Gets result of a completed job.
    *   Requirements:
        *   FIFO order.
        *   Store jobs internally until processed.
        *   Unique `job_id`.
    *   Constraints: Write *only* Python code, no explanations.

    *   Need a way to store the queue of jobs (FIFO) -> `collections.deque` or a list.
    *   Need a way to store results of jobs -> A dictionary mapping `job_id` to `result`.
    *   Need a way to track "processing". Since the prompt says "Jobs should be processed in FIFO order", I need a way to simulate the processing or provide a way to mark a job as completed.
    *   Wait, looking at the `get_result` method requirement. If `add_job` adds it and `get_result` retrieves it, but the job isn't actually "processed" by a background thread in this simple prompt, I should probably have a way to simulate the transition from "pending" to "completed".
    *   However, the prompt doesn't explicitly ask for a `process_job` method, but it implies jobs are processed. If I only have `add_job` and `get_result`, how does a job become "completed"?
    *   Actually, let's look at the signature again. `get_result` returns a result.
    *   Let's refine the internal structure:
        *   `self.queue`: A deque of `(job_id, data)`.
        *   `self.results`: A dict of `{job_id: result}`.
    *   Wait, how does a job get moved from the queue to the results?
    *   The prompt says: "Jobs should be processed in FIFO order". Usually, this implies a worker. If I don't have a `process` method, I should probably provide a way to simulate it or assume that "processing" happens via some internal logic.
    *   Let's look at the example usage:
        ```python
        job_id = queue.add_job("job1", {"task": "process_data"})
        # After processing...
        result = queue.get_result("job1")
        ```
        The `# After processing...` suggests that something external or internal completes the job.
    *   Since there's no `complete_job` method in the requirements, maybe I should implement a `process_next` method or just ensure that `get_result` can access the data if it were processed.
    *   Actually, a simple way to implement this is:
        1. `add_job` puts it in a list.
        2. `get_result` looks it up.
    *   Wait, if I want to respect "FIFO" and "processed", there should be a mechanism to actually process them.
    *   Let's reconsider the requirements:
        - `add_job`: returns ID.
        - `get_result`: returns result.
    *   If I only have those two methods, then `add_job` must initiate something and `get_result` must see the end state.
    *   Perhaps a helper method `process_jobs` or `process_next` is expected? Or perhaps the user wants me to implement a simple processing loop?
    *   Actually, often in these coding challenges, if they don't specify a `process` method, they might want a `process_all` or similar, but the prompt says "Write *only* the Python code".
    *   Let's look at the requirement: "Jobs should be processed in FIFO order". This implies that the internal state must manage the sequence.
    *   Let's provide a `process_next` method even if not explicitly required to make it functional, or simply have a dictionary for results.
    *   Actually, let's stick strictly to the requirements.
    *   If I have `add_job` and `get_result`, how does a job get a result? I'll add a `complete_job` or similar? No, the prompt says "Create a JobQueue class with the *following* methods". It doesn't say "only" these methods, but usually it's implied.
    *   Actually, if I want to show "FIFO", I'll have a queue of IDs.
    *   Maybe the prompt implies that `get_result` is called *after* some internal processing?
    *   Let's try this:
        - `self.queue`: `collections.deque` of `job_id`.
        - `self.jobs`: `dict` of `{job_id: data}`.
        - `self.results`: `dict` of `{job_id: result}`.
        - I'll add a `process_next_job` method to actually move stuff from `jobs` to `results`. Or I'll just make `get_result` handle it? No, FIFO means I should process them one by one.

    *   Let's look at common patterns for these tasks.
    *   Requirement 3: "The queue should store jobs internally until they are processed".
    *   Requirement 2: "Jobs should be processed in FIFO order".
    *   Requirement 1: `add_job` and `get_result`.

    Maybe I'll implement a `process_jobs` method to satisfy the "processed" requirement, or I can make `get_result` trigger the processing of the next job in the queue if it's not done. But `get_result` takes a specific `job_id`.

    Let's go with:
    - `self.queue`: `deque` of `job_id`s.
    - `self.data`: `dict` of `job_id` -> `data`.
    - `self.results`: `dict` of `job_id` -> `result`.
    - I'll include a `process_next_job` method to satisfy the "processed in FIFO" part. Even if not in the list of methods, it's necessary for the logic to work. Wait, the prompt says "Create a JobQueue class with the **following** methods". Usually, this means *only* those methods.

    If I only have those two methods, how does a job get completed?
    Maybe `add_job` adds it to a list, and I should have a way to mark it as done.
    Let's look at the example: `# After processing...`. This implies the processing happens outside the `JobQueue` class or is an implicit step.
    If I just want to satisfy the requirements as written:
    1. `add_job` adds to a `deque`.
    2. `get_result` checks a `results` dictionary.
    3. I need a way to put something into the `results` dictionary.

    Wait, I will implement a `process_next` method because otherwise the class is useless, but I'll make sure the two required methods are there.

    Actually, looking at the prompt again:
    `add_job(job_id: str, data: dict) -> str`
    `get_result(job_id: str) -> dict | None`

    Let's assume the "processing" is a simple transformation of the data.

    Revised Plan:
    - `self.queue`: `deque` of `(job_id, data)`.
    - `self.results`: `dict` of `job_id` -> `result`.
    - `add_job`: adds to `self.queue`.
    - `process_next_job`: Pops from `self.queue`, performs a dummy "process", puts in `self.results`.
    - `get_result`: looks in `self.results`.

    Wait, the prompt says "Jobs should be processed in FIFO order". If I don't provide a way to process them, I can't fulfill that requirement. I'll include a `process_next_job` method.

    Let's refine the "unique job_id" part. The user passes `job_id` in `add_job`. So the `job_id` is provided by the user. I should probably check if it's unique.

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

    class JobQueue:
        def __init__(self):
            self.queue = deque()
            self.results = {}
            self.active_jobs = {} # To track what's in queue

        def add_job(self, job_id: str, data: dict) -> str:
            if job_id in self.results or job_id in self.active_jobs:
                # Though the prompt doesn't say what to do if not unique,
                # usually we just allow it or handle it.
                pass
            self.queue.append((job_id, data))
            self.active_jobs[job_id] = data
            return job_id

        def process_next_job(self):
            if self.queue:
                job_id, data = self.queue.popleft()
                # Simulate processing
                result = {"status": "completed", "original_data": data}
                self.results[job_id] = result
                del self.active_jobs[job_id]

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

    Actually, if I want to be very strictly compliant with the prompt's method list, I should probably just have those two. But how does "processing" happen?
    Maybe the prompt implies that the `JobQueue` *should* process them?

    Let's look at the requirement again: "Jobs should be processed in FIFO order".
    If I don't have a `process` method, I can't satisfy this.
    I will provide a `process_jobs` method and the two required ones.

    Wait, there's a simpler interpretation. Maybe `get_result` is expected to trigger the processing? No, that's not FIFO.

    Let's try a different approach.
    Maybe `add_job` puts it in a `deque`.
    And there is a separate `process_next` method.

    Actually, I'll just implement exactly what's asked. If the user wants to process them, they can call a process method I provide.

    One detail: "The queue should store jobs internally until they are processed".

    ```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) -> None:
            if self._queue:
                job_id, data = self._queue.popleft()
                # Simulate processing logic
                self._results[job_id] = {"result": data.get("task"), "status": "success"}

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

    Wait, I'll just include `process_next`. It makes the "FIFO" requirement meaningful.

    Let's check the prompt's example:
    ```python
    job_id = queue.add_job("job1", {"task": "process_data"})
    # After processing...
    result = queue.get_result("job1")
    ```
    The `# After processing...` is a comment in the example usage. It implies that the "processing" happens *between* `add_job` and `get_result`. This means the `JobQueue` class doesn't necessarily need a `process` method, but the internal storage must preserve FIFO.

    If I don't have a `process` method, how does the `result` get into `self._results`?
    Maybe the `JobQueue` is supposed to have a way to complete a job?
    But the prompt says "Create a JobQueue class with the **following** methods".

    Wait! If I have only `add_job` and `get_result`, and I need to support "processing" in FIFO order, maybe I should have a `complete_job` method? But it's not in the list.

    Okay, let's look at the requirements again.
    1. `add_job`
    2. `get_result`
    3. FIFO order.
    4. Store internally until processed.

    Maybe the `JobQueue` is intended to be used with a worker?
    If a worker calls `queue.pop_next_job()`, that would be FIFO.
    But `pop_next_job` isn't in the list.

    Let's think. If I'm the user, and I see "Jobs should be processed in FIFO order", I expect that when the queue is "processed", it happens in order.

    Let's try to implement it such that `add_job` adds to a list, and I'll add a `process_next_job` method to actually perform the FIFO processing, even though it wasn't strictly in the list of "following methods" (it's often implied that you can add auxiliary methods). Or, I can implement `process_next_job` as a method that the user is expected to call.

    Actually, I'll provide a simple `process_next_job` method.

    One more thing: `job_id` is returned by `add_job`. The user provides `job_id` as an argument?
    `add_job(job_id: str, data: dict) -> str`
    Wait, if the user provides `job_id`, why does it say "Each job has a unique job_id that is returned when added"?
    If I provide `job_id` to the function, it's already unique if I say it is.
    But usually, the function *generates* the ID.
    However, the signature says `job_id: str` is an input.
    "Each job has a unique job_id that is returned when added".
    This means even if the user provides it, the system must ensure/return it.

    Let's look at the signature again: `add_job(job_id: str, data: dict) -> str`
    This signature means the user *provides* the `job_id`.

    Okay, let's write the code.

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

    class JobQueue:
        def __init__(self):
            self._queue: deque[tuple[str, dict]]] = deque()
            self._results: Dict[str, dict] = {}

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

        def process_next_job(self) -> None:
            """
            Processes the next job in the FIFO queue.
            This method is included to fulfill the 'processed in FIFO' requirement.
            """
            if self._queue:
                job_id, data = self._queue.popleft()
                # Simple processing logic: return the data with a 'processed' flag
                self._results[job_id] = {"status": "completed", "data": data}

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

    ```

    Wait, I should check if the prompt allows `process_next_job`. It says "Create a JobQueue class with the following methods", which usually means "only these methods".
    If I only have `add_job` and `get_result`, then `get_result` is the only way to interact with the results.
    If I can't call `process_next_job`, then how does the result get set?

    Maybe `get_result` should check if the job is processed, and if not, it processes it? No, that's not FIFO if `get_result` is called for a specific ID.

    What if "processed" is done by the user? But then the `JobQueue` doesn't know the result.
    The prompt says: "The queue should store jobs internally until they are processed".
    This implies the `JobQueue` class manages the processing.

    Let's consider a different approach. A `JobQueue` that has a `process_all` or `process_next` method is standard. I'll include `process_next_job` but I'll make sure the required methods are primary.

    Actually, I'll just implement the two requested methods and a `process_next_job` method.

    Final structure:
    - `__init__`: `deque` for queue, `dict` for results.
    - `add_job`: appends to deque, returns id.
    - `process_next_job`: pops from deque, puts into results.
    - `get_result`: gets from results.

    Wait, I just noticed the `job_id` input in `add_job`.
    `add_job(job_id: str, data: dict) -> str`
    If the user provides the ID, I don't need to generate one.

    Wait, what if I make `get_result` automatically process the next job if the requested one isn't done? No, that violates FIFO if the user asks for `job_id` which is not next.

    Let's stick to the most logical interpretation:
    The user wants a FIFO queue where jobs are added and eventually processed.
    I will provide `process_next_job` to make it functional.

    Actually, let's look at the phrasing: "Each job has a unique job_id that is returned when added".
    If the user provides it, it's unique (if they ensure it).

    One more check: "Write only the Python code, no explanations."

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

    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) -> None:
            if self._queue:
                job_id, data = self._queue.popleft()
                # Simulate some processing
                self._results[job_id] = {"status": "completed", "data": data}

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

    Wait, I'll remove the `process_next_job` docstring to keep it clean.
    Actually, I'll rename `process_next_job` to `process_next` to be concise.

    Actually, I'll stick to the requested methods and add `process_next` as a helper.

    One last check on "unique job_id". If I just take it as an argument, I don't have to do anything to make it unique.

    Is there any other interpretation?
    Maybe `add_job` should generate the ID?
    `add_job(job_id: str, data: dict) -> str`
    The signature says `job_id` is an input. If it's an input, the user is responsible for uniqueness. But I should probably check it.
    Actually, I'll just store it.

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

    class JobQueue:
        def __init__(self):
            self._queue: deque[tuple[str, dict]]] = deque()
            self._results: Dict[str, dict]] = {}

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

        def process_next(self) -> None:
            if self._queue:
                job_id, data = self._queue.popleft()
                # Placeholder for actual processing logic
                self._results[job_id] = {"status": "completed", "result": data}

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

    Wait, I'll check if `job_id` is already in `self._results`.
    Actually, let's keep it simple.

    One more look at the prompt:
    "The queue should store jobs internally until they are processed"
    This means I shouldn't delete them from the `deque` until `process_next` is called.
    "Jobs should be processed in FIFO order"
    This means `process_next` must pop from the left of the `deque`.

    Okay, code time.
</reasoning_content>

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

class JobQueue:
    def __init__(self):
        # Internal queue to store jobs in FIFO order (deque for O(1) pops from left)
        self._queue: deque[tuple[str, dict]]] = deque()
        # Dictionary to store results of completed jobs
        self._results: Dict[str, dict]] = {}

    def add_job(self, job_id: str, data: dict) -> str:
        """
        Add a job to the queue.
        :param job_id: A unique identifier for the job.
        :param data: The data/payload associated with the job.
        :return: The job_id.
        """
        self._queue.append((job_id, data))
        return job_id

    def process_next_job(self) -> None:
        """
        Processes the next job in the queue (FIFO).
        This method transitions a job from the queue to the results dictionary.
        """
        if self._queue:
            job_id, data = self._queue.popleft()
            # Simulate processing logic
            self._results[job_id] = {
                "status": "completed",
                "processed_data": data
            }

    def get_result(self, job_id: str) -> dict | None:
        """
        Get the result of a completed job.
        :param job_id: The unique identifier of the job.
        :return: The result dictionary or None if not completed.
        """
        return self._results.get(job_id)
```
</content>