<reasoning_content>
Thinking Process:

1.  **Analyze the Request:**
    *   Goal: Implement a basic job queue in Python.
    *   Class: `JobQueue`.
    *   Methods:
        *   `add_job(job_id: str, data: dict) -> str`: Add job, return `job_id`.
        *   `get_result(job_id: str) -> dict | None`: Get result of completed job.
    *   Constraints:
        *   FIFO processing.
        *   Store jobs internally until processed.
        *   Unique `job_id`.
    *   Output: Only Python code, no explanations.

2.  **Determine Implementation Details:**
    *   *Queue Structure:* A standard `queue.Queue` or `collections.deque` could work for the waiting jobs. However, since the requirement is to return a result later, I need a way to store completed jobs/results.
    *   *Processing:* The prompt implies a "basic" job queue. It doesn't explicitly mandate a background worker thread, but a job queue usually implies some mechanism to process jobs. Since it's a "basic" implementation and no threading logic is specified, I should simulate the processing mechanism or provide a way for jobs to be "processed".
    *   *Interpretation of "Processed":*
        *   Option A: The user calls a `process()` method that iterates through the queue and simulates work.
        *   Option B: Jobs are processed asynchronously (e.g., using a thread pool).
        *   Option C: The `JobQueue` just stores jobs and results, and the "processing" part is abstracted or simulated within the class (e.g., a method to simulate execution).
    *   *Refining the Requirement:* The example usage shows `add_job` then `get_result`. It doesn't show a `process` call. However, if a job is added, it shouldn't be immediately available as a result unless it's processed.
    *   *Simplest Approach:*
        1.  Store pending jobs in a queue (deque).
        2.  Store completed jobs/results in a dictionary (job_id -> result).
        3.  To make it functional, I need a mechanism to transition jobs from pending to completed.
        4.  Since the prompt asks for a "basic job queue" and doesn't specify a worker thread class, I will include a `process()` method internally or assume the user will call a method to simulate processing.
        5.  Actually, looking at the requirements: `add_job` returns `job_id`. `get_result` returns result or None.
        6.  To make `get_result` return something meaningful, the job must be processed. I will add a private method or a public `process()` method to simulate the execution of jobs in the queue.
        7.  Let's stick to the simplest interpretation: The class manages state. I'll add a `process_jobs()` method to trigger the FIFO processing. Or, I can make the queue process automatically? No, that requires threads.
        8.  Let's implement a `process()` method that processes one job or all pending jobs. Given the "basic" requirement, I'll implement a `process()` method that executes the next job in the queue and stores the result.
        9.  Wait, the prompt asks for `JobQueue` with specific methods. It doesn't strictly forbid adding helper methods like `process()`, but I should focus on the required ones.
        10. To make the example usage valid (`add_job` -> `get_result`), there must be a way to get the result. If I don't process it, `get_result` returns `None`.
        11. I will add a `process()` method to simulate the background work so the example makes sense.
        12. Structure:
            *   `self._pending_jobs`: `collections.deque`
            *   `self._results`: `dict`
            *   `self._jobs`: `dict` (to store data if needed, though `get_result` implies the result is distinct from input data).
            *   `add_job`: Store in pending, return ID.
            *   `get_result`: Look up in results.
            *   `process`: Iterate pending, compute (simulate), store in results.

    *   *Refinement on `add_job`*: The signature says `job_id: str`. Usually, `add_job` generates the ID. But the signature says `job_id: str`. This implies the caller might provide the ID or the method accepts it. The requirement says "Each job has a unique job_id that is returned when added". This contradicts the signature `add_job(job_id: str, data: dict) -> str`.
    *   *Re-reading Requirement 1*: `add_job(job_id: str, data: dict) -> str`.
    *   *Re-reading Requirement 3*: "Each job has a unique job_id that is returned when added".
    *   *Conflict Resolution*: The signature provided in the requirements (`add_job(job_id: str, ...)`) suggests the ID is an input. But the text says "returned when added". Usually, this means the method generates it. However, strict adherence to the signature `add_job(job_id: str, ...)` means I must accept an ID.
    *   *Correction*: If I accept `job_id` as input, I must ensure uniqueness. If the input `job_id` is used, I return it. If the requirement implies I generate it, the signature should be `add_job(data: dict) -> str`.
    *   *Strict Interpretation*: I will follow the provided signature: `add_job(job_id: str, data: dict) -> str`. I will validate uniqueness. If the ID exists, raise error or overwrite? Usually, unique means generate. But if the signature forces input, I will check uniqueness.
    *   *Wait, looking at the Example Usage*: `job_id = queue.add_job("job1", {"task": "process_data"})`. This confirms the signature `add_job(job_id: str, data: dict)`.
    *   So, `job_id` is passed in, validated for uniqueness, stored, and returned.

    *   *Processing Logic*: Since there's no explicit `process()` method requested in the list, but `get_result` needs data, I need a mechanism to mark jobs as done.
    *   To make the code runnable and logical, I will add a `process()` method (or `process_all()`) to simulate the worker. Without it, `get_result` will always be `None` unless the user implements their own worker.
    *   Let's add a `process()` method to the class to fulfill the "processed" aspect.

    *   *Implementation Plan*:
        1.  Import `collections.deque`.
        2.  Class `JobQueue`.
        3.  Init: `self._queue`, `self._results`, `self._processed_ids`.
        4.  `add_job`: Check if ID exists. If not, add to queue, store data, return ID.
        5.  `get_result`: Check if ID is in results, return result, else None.
        6.  `process`: Pop from queue, simulate work (return data), store in results.

3.  **Drafting Code:**

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

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

    def add_job(self, job_id: str, data: dict) -> str:
        if job_id in self._job_data:
            raise ValueError(f"Job {job_id} already exists")
        self._queue.append(job_id)
        self._job_data[job_id] = data
        return job_id

    def process(self):
        # Simulate processing jobs in FIFO order
        while self._queue:
            job_id = self._queue.popleft()
            # Simulate work by storing the data as result
            # In a real scenario, this would be an external worker
            self._results[job_id] = self._job_data.pop(job_id)

    def get_result(self, job_id: str) -> Optional[dict]:
        return self._results.get(job_id)
```
    *Wait, the prompt asks for specific methods.* It lists `add_job` and `get_result`. It doesn't explicitly forbid adding `process`, but I should ensure the core logic fits the description.
    The example shows `add_job` then `get_result`. If `process` isn't called, `get_result` returns `None`. This is acceptable behavior for a queue until processed.
    However, often "Job Queue" implies the mechanism is part of the class. I will include `process` to make it functional.
    Wait, strictly speaking, `get_result` signature is `-> dict | None`.
    I need to make sure I don't violate the type hints.

    *Refining `add_job`*: The example shows `job_id` passed as "job1".
    The logic needs to ensure uniqueness.
    I will add a `process` method because a queue needs a way to move items from "pending" to "completed" for `get_result` to work.

    *One more check*: "The queue should store jobs internally until they are processed". This confirms the separation of pending and completed (results).

    *Final Code Structure*:
    - Imports.
    - Class definition.
    - `__init__`.
    - `add_job`.
    - `process` (Helper to simulate execution so `get_result` works).
    - `get_result`.

    *Self-Correction on `process`*: The prompt didn't explicitly ask for a `process` method, but without it, the queue is static. To demonstrate FIFO and processing, `process` is necessary. I will include it.

    *Wait, one detail in `add_job`*: "return job_id". The input is `job_id`. So I return the input.
    Uniqueness check: If I add "job1" twice, the second one should fail or overwrite? Requirement says "Each job has a unique job_id". I'll raise an error on duplicate.

    Let's write the code.

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

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

    def add_job(self, job_id: str, data: dict) -> str:
        if job_id in self._job_data:
            raise ValueError(f"Job ID '{job_id}' already exists")
        self._queue.append(job_id)
        self._job_data[job_id] = data
        return job_id

    def process(self):
        """Process all pending jobs in FIFO order."""
        while self._queue:
            job_id = self._queue.popleft()
            if job_id in self._job_data:
                data = self._job_data[job_id]
                # Simulate job completion
                self._results[job_id] = data
                del self._job_data[job_id]

    def get_result(self, job_id: str) -> Optional[dict]:
        return self._results.get(job_id)
```
    Wait, `get_result` return type `dict | None` matches `Optional[dict]`.
    The prompt asks for `dict | None`. In Python 3.10+, this syntax works. In older versions, `Optional[dict]` is standard. I'll use `dict | None` in type hinting to match the prompt's style if possible, or standard typing. Since I'm writing raw code, I'll use standard typing imports to be safe, or just type hints compatible with modern Python. The prompt uses `dict | None` in the text description. I'll use `Optional[Dict[str, dict]]` for compatibility or just `dict | None` if I assume Python 3.10+. Given it's a general request, standard typing is safer. However, the prompt uses `dict | None` in the text. I will use `Optional[dict]` for the type hint to be safe across versions, or `dict | None` if I assume modern python. Let's stick to standard `typing` module for robustness unless I want to match the prompt exactly. The prompt asks for "Python code". I will use `from typing import Optional` and `Optional[dict]`. Or `dict | None` if I assume 3.10+. Let's use `Optional` to be safe.
    Actually, I'll just use `Optional[dict]`.

    Wait, I should check if I need to import `Optional`. Yes.
    Also, the prompt example:
    ```python
    queue = JobQueue()
    job_id = queue.add_job("job1", {"task": "process_data"})
    # After processing...
    result = queue.get_result("job1")
    ```
    This implies I need to make sure the code is runnable.
    I will add the `process` method.

    One nuance: `add_job` returns `str`.
    I will implement exactly as requested.

    Wait, `get_result` return type in prompt: `dict | None`.
    I will use `Optional[dict]` to ensure compatibility, or `dict | None` if I assume 3.10+. I will use `Optional[dict]` to be safe.

    Wait, I should check if `process` is required. The prompt says "Jobs should be processed... The queue should store jobs internally until they are processed". It doesn't explicitly demand a `process` method, but implies the state changes. I will add a `process` method to make the functionality complete.

    Let's refine the `process` method to be clear.
    And handle the uniqueness.

    Final check on constraints:
    1. `JobQueue` class.
    2. `add_job(job_id: str, data: dict) -> str`.
    3. `get_result(job_id: str) -> dict | None`.
    4. FIFO.
    5. Store internally until processed.
    6. Unique ID.

    I will write the code now.

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

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

    def add_job(self, job_id: str, data: dict) -> str:
        if job_id in self._job_data:
            raise ValueError(f"Job ID '{job_id}' already exists")
        self._queue.append(job_id)
        self._job_data[job_id] = data
        return job_id

    def process(self):
        while self._queue:
            job_id = self._queue.popleft()
            if job_id in self._job_data:
                self._results[job_id] = self._job_data[job_id]
                del self._job_data[job_id]

    def get_result(self, job_id: str) -> Optional[dict]:
        return self._results.get(job_id)
```
    Wait, `Optional` is not in the prompt's explicit signature text (it used `dict | None`). I will use `dict | None` in the type hint to match the prompt's style if possible, but `typing.Optional` is more standard for "Python code". I'll use `Optional` and import it.
    Actually, to be most compatible and clean, I will use `Optional[dict]`.
    Wait, the prompt asked for `dict | None` in the text description. I will stick to standard typing for the actual code type hints to ensure it runs on standard environments, but I'll make sure the logic holds.
    Actually, I can just use `dict | None` if I assume Python 3.10+. It's safer to use `Optional` for broader compatibility. I'll use `Optional`.

    Wait, I need to make sure I don't add unnecessary explanations.
    I'll just provide the code block.

    One small detail: `add_job` returns `job_id`. If the user provides it, I return it.
    Uniqueness: I'll check `self._job_data`.
    FIFO: `deque` `popleft`.

    Okay, ready to generate.

    Wait, I need to check if I should implement the processing loop inside `JobQueue` automatically or via a method.
    If I don't provide a `process` method, the user can't trigger processing.
    If I do, it's better.
    I'll add `process`.

    One more thing: The prompt example `job_id = queue.add_job("job1", ...)` shows the user providing the ID.
    So I don't generate it.

    Final check on imports: `collections` for `deque`. `typing` for `Optional`.

    Let's write it.

```python
import collections
from typing import Optional

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

    def add_job(self, job_id: str, data: dict) -> str:
        if job_id in self._pending_jobs:
            raise ValueError(f"Job ID '{job_id}' already exists")
        self._queue.append(job_id)
        self._pending_jobs[job_id] = data
        return job_id

    def process(self):
        while self._queue:
            job_id = self._queue.popleft()
            if job_id in self._pending_jobs:
                self._results[job_id] = self._pending_jobs[job_id]
                del self._pending_jobs[job_id]

    def get_result(self, job_id: str) -> Optional[dict]:
        return self._results.get(job_id)
```
    Wait, I should use `dict | None` in the type hint to match the prompt's `get_result` signature description exactly.
    `get_result(job_id: str) -> dict | None`
    I will update the type hint to `dict | None`.
    Also, I need to ensure `Optional` is imported if I use it, or just use `dict | None`. `dict | None` is valid in Python 3.10+. I'll use `Optional` for broader compatibility as it's standard practice in "Python code". But to match the prompt's `get_result` description, I'll use `Optional[dict]`.
    Wait, the prompt says: `get_result(job_id: str) -> dict | None`.
    I will use `Optional[dict]` in the code to be safe, as `|` union syntax requires Python 3.10+.
    Actually, I'll use `Optional` from typing.

    Wait, I'll check if `process` is strictly required. "Jobs should be processed...". If I don't have a `process` method, I can't process them. So yes.

    Okay, final check.
    Code only. No markdown around the code block? "Write only the Python code". Usually implies a code block. I will output the code block.

    Wait, I should not include markdown ticks if "Write only the Python code" means raw text. But usually, in this interface, a code block is expected. I will use a code block.
    Actually, "Write only the Python code, no explanations." usually means don't write text outside the code. I will provide the code inside a markdown block for clarity, or just the text. I'll use the markdown block as it's standard for "code".

    Wait, I'll remove the markdown ticks if I want to be strictly "only code". But standard interpretation is a code block. I'll provide the code block.

    Re-evaluating "Write only the Python code".
    Does it mean no markdown ```?
    Usually, it means no conversational text like "Here is the code:".
    I will provide the code in a block.

    One detail: `job_id` uniqueness.
    If I use `self._pending_jobs` to track, I must ensure `job_id` is unique across pending and completed?
    Usually, once completed, the ID is free? Or unique globally?
    "Each job has a unique job_id". Usually implies unique for the lifecycle of the system or at least while pending.
    I will check against `pending` and `results` to be safe, or just `pending`.
    If I allow reusing an ID after completion, that's fine.
    But to be simple, I'll check `pending` and `results`.
    Actually, simplest is just `pending`. Once processed, it moves to `results`. If I add it again, it's a new job.
    I'll check `pending` and `results` to ensure global uniqueness for simplicity.

    Wait, if I check `results`, I prevent reusing IDs that have been processed. This is safer.
    I'll check `self._results` and `self._pending_jobs`.

    Let's refine the `add_job` logic.
    Check if `job_id` in `self._results` or `self._pending_jobs`.
    If so, raise error.

    Okay.

```python
import collections
from typing import Optional

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

    def add_job(self, job_id: str, data: dict) -> str:
        if job_id in self._pending or job_id in self._results:
            raise ValueError(f"Job ID '{job_id}' is already used")
        self._queue.append(job_id)
        self._pending[job_id] = data
        return job_id

    def process(self):
        while self._queue:
            job_id = self._queue.popleft()
            if job_id in self._pending:
                self._results[job_id] = self._pending.pop(job_id)

    def get_result(self, job_id: str) -> Optional[dict]:
        return self._results.get(job_id)
```
    Wait, `dict | None` in signature vs `Optional[dict]` in code.
    I'll use `Optional` and import it.
    I will ensure the code is clean.

    Wait, I need to make sure I don't use `process` if it wasn't requested as a method, but it's necessary for the logic.
    I'll include it.

    Final check on imports. `typing.Optional`.
    Code looks good.

    Wait, I should check if the prompt implies `add_job` generates the ID.
    "Each job has a unique job_id that is returned when added".
    "add_job(job_id: str, ...)"
    This implies the ID is passed in.
    I will stick to the passed ID.

    One last thing: `get_result` returns `dict | None`.
    I will use `Optional[dict]` for the type hint.

    Ready.

    Wait, I'll remove the `process` method if I want to strictly follow the "methods" list in requirement 1.
    Requirement 1 says: "Create a `JobQueue` class with the following methods: ...". It doesn't say "only".
    So adding `process` is fine.
    However, to make the example work, `process` is needed.
    Okay.

    Wait, I can also implement `process` implicitly inside `get_result`? No, that would block.
    I'll keep `process`.

    Wait, I'll remove the markdown code block ticks if I want to be literal "Write only the Python code". But usually, it's fine. I'll output the code block.

    Wait, I'll remove the `process` method to be strictly compliant with the "following methods" list, and assume the user will handle processing externally or I simulate it?
    If I remove `process`, `get_result` will always return `None` unless I process it.
    If I don't provide a way to process it, the class is incomplete.
    I will add `process`.

    Actually, looking at "Implement a basic job queue... Jobs should be processed...".
    The implementation needs to handle the processing.
    I will add `process`.

    One detail: `job_id` uniqueness check.
    If I use `self._pending` and `self._results`.
    Okay.

    Let's write.

    Wait, I'll use `dict | None` in the type hint to match the prompt exactly.
    `from __future__ import annotations` might be needed for `|` in older python, but I'll assume 3.10+.
    I'll use `Optional` to be safe.

    Wait, I will use `Optional` from `typing`.

    Okay.

</reasoning_content>

<content>
```python
import collections
from typing import Optional

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

    def add_job(self, job_id: str, data: dict) -> str:
        if job_id in self._pending_jobs or job_id in self._results:
            raise ValueError(f"Job ID '{job_id}' already exists")
        self._queue.append(job_id)
        self._pending_jobs[job_id] = data
        return job_id

    def process(self):
        while self._queue:
            job_id = self._queue.popleft()
            if job_id in self._pending_jobs:
                self._results[job_id] = self._pending_jobs.pop(job_id)

    def get_result(self, job_id: str) -> Optional[dict]:
        return self._results.get(job_id)
```
</content>