<reasoning_content>
The user wants a basic job queue implementation in Python.
Requirements:
1. `JobQueue` class
2. `add_job(job_id: str, data: dict) -> str` method
3. `get_result(job_id: str) -> dict | None` method
4. FIFO order processing
5. Internal storage of jobs
6. Unique job_id returned
7. Example usage provided

I need to implement a `JobQueue` class that:
- Stores jobs internally (probably a queue/data structure)
- Has a method to add jobs with an ID and data
- Has a method to get results of completed jobs
- Processes jobs in FIFO order (I should probably include a process method or assume the user will handle processing, but the example shows `# After processing...` so I should probably include a way to process jobs, or at least make the structure ready for it. Actually, the requirements don't explicitly ask for a process method, but it says "Jobs should be processed in FIFO order" and "The queue should store jobs internally until they are processed". I'll add a `process()` method or `process_all()` method to make it functional, or I can just implement the storage and retrieval, and maybe a simple synchronous processor for completeness. Let's stick closely to the requirements: `add_job`, `get_result`. I'll add a `process()` method that processes the next job, or `process_all()`. Actually, a simple synchronous implementation would be fine.

Let's think about the internal structure:
- A dictionary to map job_id to job data and status/result
- A queue (collections.deque) to maintain FIFO order
- `add_job`: assigns job_id (if not provided? The signature says `job_id: str`, so it's provided), stores it in dict and queue
- `get_result`: returns result if completed, else None
- I should also add a method to simulate processing, or just make it so the user can call a process method. The prompt says "Jobs should be processed in FIFO order", so I'll add a `process()` method that takes the next job and marks it as completed with a result. For simplicity, I'll make `process()` return the result or just mark it done. Actually, I can make `process_all()` or just a simple `process()` that processes one job. Or I can make the class self-contained with a `process()` method that simulates work.

Wait, the example shows:
```python
queue = JobQueue()
job_id = queue.add_job("job1", {"task": "process_data"})
# After processing...
result = queue.get_result("job1")
```
It doesn't show how processing happens. I'll add a `process()` method that processes the next job in FIFO order and stores the result. I'll make it simple: `process()` pops the next job, simulates processing (maybe just returns the data as result), and stores it. Or I can just implement the storage and retrieval, and leave processing abstract, but that might not satisfy "Jobs should be processed in FIFO order". I'll implement a simple `process()` method.

Actually, a common pattern for such basic queues is to have a `process()` method that processes one job, or `process_all()`. I'll implement `process()` that processes the next job and returns its result, or just marks it done. To keep it simple, I'll store results in a dict, and when a job is processed, I'll store `{"status": "completed", "data": data}` or something similar.

Let's refine:
```python
import collections

class JobQueue:
    def __init__(self):
        self._queue = collections.deque()
        self._jobs = {}
        
    def add_job(self, job_id: str, data: dict) -> str:
        self._jobs[job_id] = {"data": data, "status": "pending", "result": None}
        self._queue.append(job_id)
        return job_id
        
    def get_result(self, job_id: str) -> dict | None:
        if job_id in self._jobs and self._jobs[job_id]["status"] == "completed":
            return self._jobs[job_id]["result"]
        return None
        
    def process(self):
        if not self._queue:
            return None
        job_id = self._queue.popleft()
        job = self._jobs[job_id]
        # Simulate processing
        job["status"] = "completed"
        job["result"] = {"status": "success", "data": job["data"]}
        return job["result"]
```

Wait, the requirement says `get_result(job_id: str) -> dict | None`. It doesn't specify what the result should look like. I'll keep it simple.
Also, the example shows `job_id = queue.add_job("job1", {"task": "process_data"})`. Note that the first argument is named `job_id` in the signature but in the example it's passed as a positional argument `"job1"`. That's fine.

Should I handle duplicate job_ids? The requirement says "Each job has a unique job_id that is returned when added". I'll assume the caller provides unique IDs, or I could generate one if not provided, but the signature requires `job_id: str`. I'll just store it as provided.

Let's stick to the exact signature: `add_job(job_id: str, data: dict) -> str`
I'll add a `process()` method to actually process jobs in FIFO order, as required. Or maybe `process_all()`? I'll just add `process()` that processes one job. Actually, the requirement says "Jobs should be processed in FIFO order", which is a property of the queue. I'll implement a `process()` method.

Wait, maybe I should just implement the queue without a process method, and assume the user will handle processing? But then how are results stored? The example has `# After processing...` which implies processing happens externally or via a method. I'll add a `process()` method for completeness.

Alternatively, I can make `get_result` trigger processing? No, that's not standard.
I'll just add a `process()` method that processes the next job and stores the result.

Let's reconsider the exact wording: "The queue should store jobs internally until they are processed". This implies I need a way to process them. I'll add a `process()` method.

Actually, a simpler approach: I'll just implement the storage and retrieval. For processing, I'll add a `process()` method that pops from the queue, processes it (simulated), and stores the result. That satisfies FIFO.

Let's write it out cleanly:

```python
import collections

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

    def add_job(self, job_id: str, data: dict) -> str:
        self._jobs[job_id] = {"data": data, "status": "pending", "result": None}
        self._queue.append(job_id)
        return job_id

    def get_result(self, job_id: str) -> dict | None:
        job = self._jobs.get(job_id)
        if job and job["status"] == "completed":
            return job["result"]
        return None

    def process(self) -> dict | None:
        if not self._queue:
            return None
        job_id = self._queue.popleft()
        job = self._jobs[job_id]
        job["status"] = "completed"
        job["result"] = {"status": "completed", "data": job["data"]}
        return job["result"]
```

Wait, the example shows:
```python
queue = JobQueue()
job_id = queue.add_job("job1", {"task": "process_data"})
# After processing...
result = queue.get_result("job1")
```
It doesn't show `queue.process()`. Maybe I should just make `process()` optional or add a `process_all()`? Or maybe the prompt expects me to just implement the storage and retrieval, and the processing part is just a requirement description. I'll stick with `process()` method.

Actually, I can make `get_result` not depend on a separate process call if I want, but that's not standard. I'll keep `process()` as is.

Wait, the requirement says: "Jobs should be processed in FIFO (First-In-First-Out) order". This is a behavioral requirement. I'll add a `process()` method. To be safe, I'll also add a `process_all()` method that processes all pending jobs, or just leave it as `process()`.

Actually, many simple queue implementations just have `enqueue` and `dequeue`. Here it's `add_job` and `get_result`. I'll add a `process()` method.

Let's check types: `dict | None` is Python 3.10+ syntax. I'll use it as requested.

One thing: `job_id` in the example is passed as a positional argument. The signature `add_job(job_id: str, data: dict) -> str` matches.

I'll refine the code to be concise and match exactly.

```python
import collections

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

    def add_job(self, job_id: str, data: dict) -> str:
        self._queue.append(job_id)
        self._results[job_id] = {"status": "pending", "data": data, "result": None}
        return job_id

    def get_result(self, job_id: str) -> dict | None:
        job = self._results.get(job_id)
        if job and job["status"] == "completed":
            return job["result"]
        return None

    def process(self) -> dict | None:
        if not self._queue:
            return None
        job_id = self._queue.popleft()
        job = self._results[job_id]
        job["status"] = "completed"
        job["result"] = {"status": "success", "data": job["data"]}
        return job["result"]
```

Wait, should `process()` be required? The prompt doesn't explicitly ask for it, but says "Jobs should be processed in FIFO order". I'll include it. Alternatively, I could make the queue automatically process jobs if I add a method, but synchronous processing is fine.

Actually, I realize that `dict | None` syntax is valid in Python 3.10+. I'll keep it.

Let's consider if the prompt expects a simpler implementation without `process()`. Sometimes these prompts just want the storage and retrieval, and assume the user will handle processing. But "Jobs should be processed in FIFO order" strongly implies the queue should manage processing. I'll keep `process()`.

To be extremely safe, I'll make `process()` process one job, and maybe add a comment or just leave it. The code is clean.

One minor thing: `get_result` returns `dict | None`. I'll make sure the type hint matches.

I'll write the final code.

```python
import collections

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

    def add_job(self, job_id: str, data: dict) -> str:
        self._jobs[job_id] = {"data": data, "status": "pending", "result": None}
        self._queue.append(job_id)
        return job_id

    def get_result(self, job_id: str) -> dict | None:
        job = self._jobs.get(job_id)
        if job and job["status"] == "completed":
            return job["result"]
        return None

    def process(self) -> dict | None:
        if not self._queue:
            return None
        job_id = self._queue.popleft()
        job = self._jobs[job_id]
        job["status"] = "completed"
        job["result"] = {"status": "completed", "data": job["data"]}
        return job["result"]
```

Wait, should I handle the case where `job_id` is already present? The requirement says "Each job has a unique job_id", so I'll assume uniqueness.

The example usage doesn't show `process()`, just comments. I'll add `process()` as it's necessary to actually process jobs. Alternatively, I could make `process_all()` but `process()` is fine.

Actually, I can make it so that `get_result` doesn't require a separate process call if I want, but that's not standard. I'll stick with `process()`.

One more thing: the prompt says "Write only the Python code, no explanations." So I'll output just the code block.

I'll double check the requirements:
1. `JobQueue` class with `add_job` and `get_result`
2. FIFO order
3. Stores internally until processed
4. Unique job_id returned

All met. I'll provide the code.
I'll make sure type hints are correct. `dict | None` is fine.
I'll use `typing.Optional` if needed, but `dict | None` is standard in 3.10+. I'll stick with `dict | None`.

Final code:
```python
import collections

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

    def add_job(self, job_id: str, data: dict) -> str:
        self._jobs[job_id] = {"data": data, "status": "pending", "result": None}
        self._queue.append(job_id)
        return job_id

    def get_result(self, job_id: str) -> dict | None:
        job = self._jobs.get(job_id)
        if job and job["status"] == "completed":
            return job["result"]
        return None

    def process(self) -> dict | None:
        if not self._queue:
            return None
        job_id = self._queue.popleft()
        job = self._jobs[job_id]
        job["status"] = "completed"
        job["result"] = {"status": "success", "data": job["data"]}
        return job["result"]
```

This looks solid. I'll output it.
Wait, should I include `process()`? The requirements don't explicitly list it, but say "Jobs should be processed in FIFO order". It's implied. I'll keep it. If they wanted just storage, they wouldn't mention processing order. I'll add it.

Actually, to be strictly compliant with "Write only the Python code", I'll just provide the class. I'll make sure it's complete.

One minor adjustment: I'll use `typing.Dict` and `typing.Optional` for broader compatibility, or just stick to `dict | None` as requested. The prompt uses `dict | None`, so I'll keep it.

All good.
Output matches requirement.
Proceeds. 
Let's verify the example usage works with this code:
```python
queue = JobQueue()
job_id = queue.add_job("job1", {"task": "process_data"})
queue.process()
result = queue.get_result("job1")
# result is {"status": "success", "data": {"task": "process_data"}}
```
Matches expectations.
I'll output the code now. 
One thing: the prompt says `add_job(job_id: str, data: dict) -> str`. In the example, it's called as `queue.add_job("job1", {"task": "process_data"})`. That's positional, which matches.
Everything is fine.
I will produce the final answer. 
No extra text. Just the code.
Done. 
Self-Correction/Refinement during thought: 
Should I make `process()` process all jobs automatically? No, FIFO order implies sequential processing. `process()` processing one at a time is standard. I'll keep it.
What about thread safety? Not required.
What about `get_result` returning `None` if not completed? Yes.
All set. 
Output matches. 
Proceeds. 
```python
import collections

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

    def add_job(self, job_id: str, data: dict) -> str:
        self._jobs[job_id] = {"data": data, "status": "pending", "result": None}
        self._queue.append(job_id)
        return job_id

    def get_result(self, job_id: str) -> dict | None:
        job = self._jobs.get(job_id)
        if job and job["status"] == "completed":
            return job["result"]
        return None

    def process(self) -> dict | None:
        if not self._queue:
            return None
        job_id = self._queue.popleft()
        job = self._jobs[job_id]
        job["status"] = "completed"
        job["result"] = {"status": "success", "data": job["data"]}
        return job["result"]
```
Looks good. I'll output this. 
Note: I'll remove the `process` method if it's not strictly required, but the requirement "Jobs should be processed in FIFO order" implies it. I'll keep it. It's standard.
Actually, to be extremely precise, I'll just include the class with the requested methods, and add `process()` as it's necessary for the "processed" part to work. The prompt says "The queue should store jobs internally until they are processed", which implies an external or internal processing mechanism. I'll keep `process()`.
Done. 
Output matches. 
Proceeds. 
[Final Check]
- Class name: `JobQueue`
- Methods: `add_job`, `get_result`
- FIFO: `deque` ensures this
- Internal storage: `self._jobs` dict and `self._queue`
- Returns job_id: yes
- Example usage compatible: yes
- Type hints: match
- No explanations: yes
All good. 
Output generation. 
(Self-Correction/Note during generation prep)
I realize the prompt might expect a simpler implementation without `process()`, just the storage and retrieval, assuming the user will handle processing. But "Jobs should be processed in FIFO order" is a requirement for the queue itself. I'll keep `process()`. It's fine.
Actually, I'll make `process()` process one job, which is standard.
I'll output exactly the code.
Done. 
[Output Generation] -> *Proceeds*

</reasoning_content>

<content>
```python
import collections

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

    def add_job(self, job_id: str, data: dict) -> str:
        self._jobs[job_id] = {"data": data, "status": "pending", "result": None}
        self._queue.append(job_id)
        return job_id

    def get_result(self, job_id: str) -> dict | None:
        job = self._jobs.get(job_id)
        if job and job["status"] == "completed":
            return job["result"]
        return None

    def process(self) -> dict | None:
        if not self._queue:
            return None
        job_id = self._queue.popleft()
        job = self._jobs[job_id]
        job["status"] = "completed"
        job["result"] = {"status": "success", "data": job["data"]}
        return job["result"]
```
</content>