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Tag: software engineer

Five Great DevOps Job Opportunities

devopsy.kinsta.cloud is now providing a weekly DevOps jobs report through which opportunities for DevOps professionals will be highlighted as part of an effort to better serve our audience.

Our goal in these challenging economic times is to make it just that much easier for DevOps professionals to advance their careers.

Of course, the pool of available DevOps talent is still relatively constrained, so when one DevOps professional takes on a new role, it tends to create opportunities for others.

The five job postings shared this week are selected based on the company looking to hire, the vertical industry segment and naturally, the pay scale being offered.

We’re also committed to providing additional insights into the state of the DevOps job market. In the meantime, for your consideration.

Indeed.com

OpenAI
New York City
Client Platform Engineer
$255,000 to $325,000

Dice.com

Dell Technologies
Austin, TX
Principal Software Engineer
$170,000 to $220,000

LinkedIn

Jasper
Remote
DevOps Engineer
$170,000 to $200,000

The Job Network

CTG
Columbia, MD
DevOps Engineer
$120,000 to $226,000

SimplyHired.com

Viasat
Carlsbad, CA
DevOps Engineer
$111,500 to $208,000

October 20, 2025
Valory Unveils AI Software Engineer for Building Multiple Types of Agents

Valory has launched an artificial intelligence (AI) agent, dubbed Propel Genie, that is specially designed to act as a software engineer that enables application developers to create agents trained for specific descriptions defined in natural language specifications.

Originally developed to create agents for the open-source Olas framework for cryptocurrency transactions, Propel Genie presents developers with an interface similar to ChatGPT. It then translates natural language descriptions into a technical roadmap, known as a Finite State Machine (FSM) specification, that outlines the structure for the agent architecture. That roadmap is then used to generate the agent described in the specification using Genie code planner, code generation and code evaluation agents.

Valory CEO David Minarsch said Genie is essentially a super-agent that employs large language models (LLMs) to convert a design specification written in natural language to create the code that drives a fully functional autonomous AI agent. Each agent invokes different LLMs that might lend themselves better to one task than another, said Minarsch.

Genie also enables rapid prototyping through automated workflows to facilitate the swift creation of autonomous agents that developers can iteratively build, test, and refine agent prototypes as needed over a few days, he added.

Available via the Propel platform that Valory makes available for developers of crypto applications, Olas is already being used to enable multiple AI agents created using Propel Genie to interact with one another. Propel Genie, however, can also be applied more widely to enable organizations to build their own custom agents, said Minarsch.

In the long term, Valory is working toward enabling anyone to create their own AI agent by reducing the complexity. In the meantime, however, Genie essentially functions as a software engineer that enables developers of varying skill levels to create an AI agent based on a natural language specification.

Humans and AI Agents

It’s not clear how the role of software engineers will evolve in the age of AI, but many of the manual tasks are becoming increasingly automated. In the future, most DevOps teams will be made up of a mix of humans and AI agents specifically trained to handle specific tasks. The challenge will then become orchestrating workflows across a team that includes those AI agents. As the time and effort required to create new agents starts to decrease, it also becomes possible to add or replace AI agents as needed across a wide range of digital business processes.

In the short term, however, most AI tools are squarely focused on enabling developers to write more code. There is not nearly as much focus on applying AI to the workflows that DevOps teams employ to shepherd all that code into an application running in a production environment. However, with the advent of AI tools such as Genie the art of what might soon be possible is coming into sharper relief.

The one thing that remains to be seen now is the degree to which agents such as Genie might one day fundamentally change the economics of software development.

July 18, 2024
To Devin or Not to Devin?
Devin.ai is an impressive generative AI solution that claims to be a new kind of AI engineer designed to perform software engineering tasks autonomously. Cognition Labs, Devin’s creator, said Devin is capable of responding to text commands and can be assigned tasks such as assessing the benchmark performance of an application. It will then build a plan and configure the required tools using its own command line interface (CLI), code editor and browser through which it can access, read and, for example, comprehend documentation using a reasoning engine and long-term planning capability based on advances in reinforcement learning.

Those capabilities make it possible for Devin to, for example, build a website, autonomously identify and fix bugs in codebases, deploy applications and even train other AI models. But there are a number of questions yet to be answered before Devin is ready for wider adoption.

For instance, whether or not every question from an organization will be used to train Devin.ai remains to be determined. Many experts believe that some large language model implementations, with almost 2 trillion parameters, cannot be comprehended even by their creators. There are 86 billion neurons in the human brain. Now, there’s not a one-to-one comparison to the human brain, but the point is they are both complex systems. GPT-4’s neural network contains 1.7 trillion parameters. The main point is that, regardless of what anyone says about their LLM implementation, it’s reasonable to assume they don’t know how it works internally. OpenAI states in their license agreement that they do not train on client data, but it is noteworthy that they didn’t have this policy early on.

Thoughts on Devin.ai

One of Devin’s most intriguing aspects is its autonomous operation through its shell code editor and web browser. Devin AI claims to set a new benchmark in software coding, boasting the ability to pass practical engineering interviews and complete real jobs on platforms like Upwork. However, as a software engineer with 45 years of experience, I take these claims with a hefty chaser of skepticism. Devin.ai may introduce many security concerns, especially when dealing with sensitive information or performing actions on services, databases and APIs, as well as the handling of sensitive information and the potential for unintended actions. This emphasizes the importance of developing robust security measures to mitigate these risks introduced by tools like Devin.ai. While I’m not against AI, I am cautious about Devin’s potential to replace human full-stack software engineers.

Back in the Day

One of the biggest obstacles in selling hosted Chef to regulated companies in the early days was the concern that ten young kids out of Seattle would have access to systems that create billions of dollars worth of infrastructure. Are these same institutions going to trust ten kids out of Silicon Valley with Devin, which may present similar risks?

Let’s set aside the infrastructure issues for a moment. What are your opinions on the robotic process automation (RPA) revolution that has taken place in the last decade? For one, consider that it has caused a technical debt nightmare. RPAs create many one-off technical problems that can be difficult to solve. One of the great things about the DevOps movement was that it formed a bottleneck between novel ideation and managed scale while consistently proving speed and flow. I’m a huge fan of development tools like Microsoft’s Copilot for development and operations. However, like RPA, I’m deeply concerned about a tool that does both. Consider the implications of Devin.ai-generated solutions and their impact on secure software supply chains and automated governance. Organizations are spending billions of dollars trying to figure this out, and we are still in very early days as far as coming up with solutions.

Conclusion

Devin.ai is a fascinating generative AI tool that is generating a lot of well-deserved buzz in the industry. However, I recommend large organizations be cautious when using it. While monitoring ChatGPT is always a good practice in highly-regulated organizations, I suggest being extra careful when using a tool like Devin.ai. Following Devin.ai’s ideas and progress is a great idea; however, until or unless they create a bring-your-own model implementation, I would proceed cautiously. Organizations should look at useful examples to help understand how you might build your own “Devin.” Here are some resources to check out:
Devin represents a significant leap forward in the realm of AI and software development, and it is a stepping stone toward a future where AI can act as a true collaborator or co-worker rather than a replacement for human engineers. I look forward to advancements that will allow generative AI to tackle more complex, integrated systems and contribute meaningfully to the software development process.
March 28, 2024
Should You Hire a Clojure Engineer?
Quite often, when developing applications, it becomes necessary to execute long-running code at the same time as performing other tasks. More recently, to run a program on the Java virtual machine (JVM) it was necessary to write the program in Java. Those days are long gone due to the wide variety of programming languages for the JVM. Clojure is a general-purpose dynamic language developed by Rich Hickey for the JVM. One of the main goals of an engineer who speaks this language is to simplify the process of writing a program with multiple threads that are accessing data simultaneously. What, exactly, is the role of a Clojure software engineer and how can they improve the functionality of its products?

What Problems can a Clojure Software Engineer Fix?

A good programming language should help us write transparent and straightforward programs. The software systems that humans create are inherently changeable. In development, it is impossible to foresee all situations in advance, especially when the system’s complexity only grows over time. Even the slightest code change can potentially lead to significant changes in overall system behavior. As a developer, it’s necessary to study carefully, analyze the code and predict each shift’s side effects. Over time, and with greater complexity, it becomes close to impossible to thoroughly analyze all the possible consequences of our changes.

The Clojure language was created to overcome these challenges. Clojure has a more convenient and modern syntax that orients the user to the functional paradigm as much as possible. Despite the dynamic typing of the language, Clojure programs are compiled into JVM bytecode and integrate seamlessly with existing Java programs. Clojure has now been implemented for several platforms, the most notable of which are the JVM, .Net, and JavaScript. Because it runs on the JVM, Clojure code is portable, stable, reliable and secure. Each operation in Clojure is implemented in three forms: function, macro or special form.

Typically, complexities in computer programs cause side effects. This language helps to localize those and makes writing functions cleaner. This makes testing easier for the developer, too, since they don’t have to try different queues and find the correct state of the inputs.

What to Look for When Hiring

Large companies in particular value senior full-stack Clojure software engineers who can work across a number of tasks from analytics to coding, testing and DevOps.

Among the problems that a Clojure software engineer can solve for an enterprise are:
- Development of front end and back end systems
- Creation of algorithms for load distribution by competencies/user workload
- Design of modules for forecasting the load users create on systems
- Machine learning in Clojure.
Here is the example of a Clojure engineer’s résumé:

Clojure is also an expression of a developer’s ideas about how simple a programmer’s tool should be. Clojure typically uses only four data structures: list, vector, display and set. The main API is built around these four structures. The main abstraction in Clojure is a pure function that has no side effects and is therefore much more reusable.

To date, many libraries have been written for Clojure, including those for developing simple and modular web applications. A Clojure program is an open architecture constructor, which means developers can choose for themselves which libraries to use regardless of which others they may have chosen previously.

Clojure Engineer Salary

Salaries for Clojure software engineers in the U.S. average $129,887, while a Clojure software engineer’s salary in the UK is $69,910. In Canada, the typical Clojure engineer’s salary is $61,780 and in Germany, $69,089. Clojure software engineers in Ukraine earn an average salary of $38,000.

Value to the Enterprise

Enterprise software performance requirements dictate the need to use parallel computing to interact with each other and work at the same time. Existing languages are poorly suited for parallelizing tasks. They contain many object and state dependencies, which translate to systems with unpredictable behavior in parallel interactions. Solutions based on locks and traffic lights do not greatly simplify the implementation of these tasks; the fundamental problem of the system’s state’s dependency on the sequences of object interaction remains.

By using Clojure in web development, a programmer can develop using other minor, task-focused languages. ClojureScript, for example, compiles quickly to JavaScript and runs in the browser. All of this provides an entirely new approach to building client applications.

Since Clojure seamlessly integrates with any Java code and can be deployed on standard Java application servers, it is well-suited to web application development, too. The flexibility of the language and its incredible expressiveness allows developers to create fully functional web applications very quickly.

All a developer needs to work with Clojure is the JDK and the Clojure library which are contained in a single JAR file. There are two standard ways to develop and run Clojure programs: The most common way is to use a simple interactive REPL, a read-compute-print loop.

Since Clojure is a general-purpose language, it is not difficult for a programmer to find a use for it. Since it is based on the JVM, there is already a massive selection of libraries available, which significantly lowers the entry threshold for developers skilled in other languages and removes the need for developers to write code from scratch.

Clojure can be used wherever modern, efficient, stable data structures are needed. Of course, there is no one-size-fits-all tool that can handle all types of development tasks. However, the fact that a Clojure developer can use the language for client-server communication is yet another advantage.
August 10, 2021
SauceCon Speaker Profile: Phil Wells

This is the seventh in a series of articles highlighting speakers at SauceCon 2019. SauceCon brings together the global community of Sauce Labs users and continuous testing experts to learn from each other and level up their automated testing and continuous delivery skills. This year’s event will be held April 23-25 in Austin, Texas.

Phil Wells is coming to SauceCon 2019 to talk about the New York Times Crossword.

No, really, Phil is a software engineer with the web group of the New York Times Games team whose job is to build quality into the online version of the famous puzzle done by thousands of people daily.

More than anything, Phil cares about mission. During his 12 years of web development experience, he has worked on software that educates parents of kids with autism, software that helps people perform better on standardized tests and now for the New York Times, whose mission is to help people understand the world around them.

“The puzzle brings so much joy into people’s days,” says Phil. “I’m really proud of my work.”

When Phil tells people what he does for a living, they want to know what it means. Does he just solve crosswords all day? Is he in web development or game development? Does he know Will Shortz? (The answer to that last one is no, but he is an emoji in their internal Slack instance!) People love the crossword, and they all seem to want to know more about how the sausage is made.

Phil’s session at SauceCon will be all about “Automating the New York Times Crossword.” He wants to show test practitioners that testing a web application as complex as the crossword involves the same best practices as testing anything else. During his talk, Phil will show attendees some of the tricks his team used to become fast and reliable.

“The main theme of my talk is about making software development feel better. We don’t want to feel the shame of failed builds or delayed releases,” he said. “So, we built these systems to help us ship the stuff we build quickly and safely.” The first half of his talk covers the things the team did to get cultural wins internally. In the second half, Phil will dive into his particular team’s bag of tricks; the tools they use to make sure the tests are making everyone do their job better.

When he’s not working on testing the crossword, Phil enjoys improv comedy. He is also an aficionado of “The Big Lebowski,” and has written a book called “Dudesong,” an epic poem adaptation of the movie, featuring 5,500 lines of poetry in rhyming couplets!

Whether or not you’re a fan of “The Big Lebowski,” you can hear from Phil and more than 30 other expert speakers at SauceCon 2019, the third-annual Sauce Labs user conference. To see a full list of presentations or to register, visit the SauceCon website.

— Rebecca Cramer

March 7, 2019