Terraform Jobs in Honolulu.
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Software Engineer, Data Infrastructure & Acquisition - Honolulu, HI, USA
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The mission of Speechify is to make sure that reading is never a barrier to learning.
Over 50 million people use Speechify’s text-to-speech products to turn whatever they’re reading – PDFs, books, Google Docs, news articles, websites – into audio, so they can read faster, read more, and remember more. Speechify’s text-to-speech reading products include its iOS app, Android App, Mac App, Chrome Extension, and Web App. Google recently named Speechify the Chrome Extension of the Year and Apple named Speechify its 2025 Design Award winner for Inclusivity.
Today, nearly 200 people around the globe work on Speechify in a 100% distributed setting – Speechify has no office. These include frontend and backend engineers, AI research scientists, and others from Amazon, Microsoft, and Google, leading PhD programs like Stanford, high growth startups like Stripe, Vercel, Bolt, and many founders of their own companies.
Overview
We're looking to hire for our Data side of our AI team at Speechify. This role is responsible for all aspects of data collection to support our model training operations. We are able to build high-quality datasets at petabyte-scale and low cost through a tight integration of infrastructure, engineering, and research work. We are looking for a skilled Software Engineer to join us.
What You’ll Do
- Be scrappy to find new sources of audio data and bring it into our ingestion pipeline
- Operate and extend the cloud infrastructure for our ingestion pipeline, currently running on GCP and managed with Terraform.
- Collaborate closely with our Scientists to shift the cost/throughput/quality frontier, delivering richer data at bigger scale and lower cost to power our next-generation models.
- Collaborate with others on the AI Team and Speechify Leadership to craft the AI Team’s dataset roadmap to power Speechify’s next-generation consumer and enterprise products.
An Ideal Candidate Should Have
- BS/MS/PhD in Computer Science or a related field.
- 5+ years of industry experience in software development.
- Proficiency with bash/Python scripting in Linux environments
- Proficiency in Docker and Infrastructure-as-Code concepts and professional experience with at least one major Cloud Provider (we use GCP)
- Experience with web crawlers, large-scale data processing workflows is a plus
- Ability to handle multiple tasks and adapt to changing priorities.
- Strong communication skills, both written and verbal.
What we offer
- A fast-growing environment where you can help shape the company and product.
- An entrepreneurial-minded team that supports risk, intuition, and hustle.
- A hands-off management approach so you can focus and do your best work.
- An opportunity to make a big impact in a transformative industry.
- Competitive salaries, a friendly and laid-back atmosphere, and a commitment to building a great asynchronous culture.
- Opportunity to work on a life-changing product that millions of people use.
- Build products that directly impact and support people with learning differences like dyslexia, ADD, low vision, concussions, autism, and more.
- Work in one of the fastest-growing sectors of tech, the intersection of artificial intelligence and audio.
Compensation: The United States base salary range for this full-time position is $140,000-$200,000 + bonus + equity depending on experience
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Speechify is committed to a diverse and inclusive workplace.
Speechify does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
Ready to apply?
Apply to Speechify
Principal MLOps Engineer
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This is a U.S. based position. All of the programs we support require U.S. citizenship to be eligible for employment. All work must be conducted within the continental U.S.
Who we are:
Raft (https://TeamRaft.com) is a customer-obsessed non-traditional defense tech company dedicated to empowering U.S. military and government agencies with cutting-edge AI/ML and data solutions. We are a leader in autonomous data fusion and Agentic AI, with a purposeful focus on Distributed Data Systems, Platforms at Scale, and Complex Application Development. With headquarters in McLean, VA, our range of clients includes innovative federal and public agencies leveraging design thinking, cutting-edge tech stack, and cloud-native ecosystem. We build digital solutions that impact the lives of millions of Americans.
We’re looking for an experienced Principal ML Ops Engineer to support our customers and join our passionate team of high-impact problem solvers.
About the role:
Raft is building mission-critical AI and data platforms for the Department of Defense (DoD). Our systems ingest and process massive volumes of real-time data from hundreds of sensors and operational sources, transform that data into usable intelligence, and deliver it to operators through mission applications and common operational pictures that support time-sensitive decision-making.
Our platform operates at scale, processing billions of events per day with low-latency data pipelines and cloud-native infrastructure. As Raft expands its AI capabilities, we are investing in a more mature end-to-end machine learning platform to support model development, evaluation, deployment, monitoring, and lifecycle management across both cloud and constrained operational environments.
In this role, you will help design, deploy, and mature Raft’s ML platform and MLOps infrastructure. You will work across Kubernetes-based deployment environments, GPU-enabled infrastructure, model serving systems, CI/CD pipelines, and secure production operations to enable rapid and reliable delivery of machine learning capabilities. This role is ideal for someone who understands both the infrastructure needed to run ML systems in production and the practical needs of ML engineers building and deploying models.
What you’ll do:
- Design, build, and maintain secure, scalable MLOps infrastructure and deployment pipelines for production ML systems
- Help mature Raft’s internal ML platform and model lifecycle capabilities, including model packaging, registry/catalog workflows, deployment, monitoring, and operational support
- Deploy and manage machine learning workloads on Kubernetes, including GPU-enabled clusters
- Support model serving and inference infrastructure for a range of ML use cases, including traditional ML, computer vision, speech/audio, and LLM-based systems
- Build and maintain CI/CD workflows for ML services, model artifacts, and platform components
- Partner closely with ML engineers, software engineers, and product teams to move models from experimentation to reliable operational deployment
- Improve observability, reliability, security, and maintainability across ML infrastructure and services
- Help evaluate and standardize runtime patterns, serving frameworks, and deployment architectures for production ML workloads
- Contribute to infrastructure decisions across edge, on-prem, and cloud-hosted deployment environments
- Support compliance-driven deployment practices and secure software supply chain requirements in defense environments
- Get hands-on with customers at the most forward-leaning places in the Department of War
What we are looking for:
- 7+ years of relevant hands-on experience in software engineering, platform engineering, DevOps, MLOps, or related technical roles
- 5+ years of experience with Docker and Kubernetes in production environments
- 5+ years of experience supporting enterprise cloud infrastructure or applications in AWS, Azure, or similar environments
- Strong experience provisioning, operating, and troubleshooting Kubernetes clusters in production
- Experience building and maintaining machine learning platforms, infrastructure, or pipelines used by engineering or data science teams
- Practical experience deploying machine learning workloads on Kubernetes
- Experience managing clusters or workloads that use GPUs
- Strong understanding of Helm and Kubernetes deployment patterns
- Strong scripting or programming skills, preferably in Python
- Experience with modern software engineering practices including Git, CI/CD, DevOps, and Agile/Scrum workflows
- Strong troubleshooting, systems thinking, and communication skills
- Ability to work independently and collaboratively in a fast-moving environment
- Ability to obtain and maintain a Top Secret clearance
- Ability to obtain Security+ certification within the first 90 days of employment
Highly preferred:
- Experience with ML model serving and inference platforms such as Triton Inference Server, KServe, Ray Serve, vLLM, or similar technologies
- Experience with secure and compliant deployment practices in regulated or government environments
- Experience with Kubernetes-based ML platforms such as Kubeflow
- Familiarity with service mesh technologies such as Istio
- Experience provisioning and debugging complex CI/CD systems
- Experience with infrastructure as code tools such as Terraform
- Familiarity with software supply chain security, container hardening, vulnerability management, and runtime scanning
- Experience supporting ML systems across multiple deployment environments, including cloud, on-prem, and edge
- Background working with machine learning engineers on model training, evaluation, packaging, and release workflows
- Familiarity with storage and artifact systems used in ML platforms, such as S3-compatible object stores, registries, and metadata/catalog system
What success looks like:
- You help Raft stand up a more mature and repeatable ML platform for deploying and managing models in production
- ML engineers can move faster because deployment, serving, and platform workflows are clearer, more reliable, and easier to use
- Model deployments become more secure, observable, and supportable across real-world mission environments
- The organization gains stronger infrastructure for model lifecycle management, including deployment standards, runtime patterns, and platform ownership
Clearance Requirements:
- Ability to obtain and maintain a Top Secret clearance
Work Type:
- Remote in DMV; McLean, VA; Boston, MA; San Antonio, TX; Colorado Springs, CO; Tampa, FL; Honolulu, HI Locations ONLY
- May require up to 40% travel
Salary Range: $150,000.00 - $200,000.00
What we will offer you:
- Highly competitive salary
- Fully covered healthcare, dental, and vision coverage
- 401(k) and company match
- Take as you need PTO + 11 paid holidays
- Education & training benefits
- Annual budget for your tech/gadgets needs
- Monthly box of yummy snacks to eat while doing meaningful work
- Remote, hybrid, and flexible work options
- Team off-site in fun places!
- Generous Referral Bonuses
- And More!
Our Vision Statement:
We bridge the gap between humans and data through radical transparency and our obsession with the mission.
Our Customer Obsession:
We will approach every deliverable like it's a product. We will adopt a customer-obsessed mentality. As we grow, and our footprint becomes larger, teams and employees will treat each other not only as teammates but customers. We must live the customer-obsessed mindset, always. This will help us scale and it will translate to the interactions that our Rafters have with their clients and other product teams that they integrate with. Our culture will enable our success and set us apart from other companies.
How do we get there?
Public-sector modernization is critical for us to live in a better world. We, at Raft, want to innovate and solve complex problems. And, if we are successful, our generation and the ones that follow us will live in a delightful, efficient, and accessible world where out-of-box thinking, and collaboration is a norm.
Raft’s core philosophy is Ubuntu: I Am, Because We are. We support our “nadi” by elevating the other Rafters. We work as a hyper collaborative team where each team member brings a unique perspective, adding value that did not exist before. People make Raft special. We celebrate each other and our cognitive and cultural diversity. We are devoted to our practice of innovation and collaboration.
We’re an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.
Ready to apply?
Apply to Raft Company WebsitePrincipal MLOps Engineer
Share this job
This is a U.S. based position. All of the programs we support require U.S. citizenship to be eligible for employment. All work must be conducted within the continental U.S.
Who we are:
Raft (https://TeamRaft.com) is a customer-obsessed non-traditional defense tech company dedicated to empowering U.S. military and government agencies with cutting-edge AI/ML and data solutions. We are a leader in autonomous data fusion and Agentic AI, with a purposeful focus on Distributed Data Systems, Platforms at Scale, and Complex Application Development. With headquarters in McLean, VA, our range of clients includes innovative federal and public agencies leveraging design thinking, cutting-edge tech stack, and cloud-native ecosystem. We build digital solutions that impact the lives of millions of Americans.
We’re looking for an experienced Principal ML Ops Engineer to support our customers and join our passionate team of high-impact problem solvers.
About the role:
Raft is building mission-critical AI and data platforms for the Department of Defense (DoD). Our systems ingest and process massive volumes of real-time data from hundreds of sensors and operational sources, transform that data into usable intelligence, and deliver it to operators through mission applications and common operational pictures that support time-sensitive decision-making.
Our platform operates at scale, processing billions of events per day with low-latency data pipelines and cloud-native infrastructure. As Raft expands its AI capabilities, we are investing in a more mature end-to-end machine learning platform to support model development, evaluation, deployment, monitoring, and lifecycle management across both cloud and constrained operational environments.
In this role, you will help design, deploy, and mature Raft’s ML platform and MLOps infrastructure. You will work across Kubernetes-based deployment environments, GPU-enabled infrastructure, model serving systems, CI/CD pipelines, and secure production operations to enable rapid and reliable delivery of machine learning capabilities. This role is ideal for someone who understands both the infrastructure needed to run ML systems in production and the practical needs of ML engineers building and deploying models.
What you’ll do:
- Design, build, and maintain secure, scalable MLOps infrastructure and deployment pipelines for production ML systems
- Help mature Raft’s internal ML platform and model lifecycle capabilities, including model packaging, registry/catalog workflows, deployment, monitoring, and operational support
- Deploy and manage machine learning workloads on Kubernetes, including GPU-enabled clusters
- Support model serving and inference infrastructure for a range of ML use cases, including traditional ML, computer vision, speech/audio, and LLM-based systems
- Build and maintain CI/CD workflows for ML services, model artifacts, and platform components
- Partner closely with ML engineers, software engineers, and product teams to move models from experimentation to reliable operational deployment
- Improve observability, reliability, security, and maintainability across ML infrastructure and services
- Help evaluate and standardize runtime patterns, serving frameworks, and deployment architectures for production ML workloads
- Contribute to infrastructure decisions across edge, on-prem, and cloud-hosted deployment environments
- Support compliance-driven deployment practices and secure software supply chain requirements in defense environments
- Get hands-on with customers at the most forward-leaning places in the Department of War
What we are looking for:
- 7+ years of relevant hands-on experience in software engineering, platform engineering, DevOps, MLOps, or related technical roles
- 5+ years of experience with Docker and Kubernetes in production environments
- 5+ years of experience supporting enterprise cloud infrastructure or applications in AWS, Azure, or similar environments
- Strong experience provisioning, operating, and troubleshooting Kubernetes clusters in production
- Experience building and maintaining machine learning platforms, infrastructure, or pipelines used by engineering or data science teams
- Practical experience deploying machine learning workloads on Kubernetes
- Experience managing clusters or workloads that use GPUs
- Strong understanding of Helm and Kubernetes deployment patterns
- Strong scripting or programming skills, preferably in Python
- Experience with modern software engineering practices including Git, CI/CD, DevOps, and Agile/Scrum workflows
- Strong troubleshooting, systems thinking, and communication skills
- Ability to work independently and collaboratively in a fast-moving environment
- Ability to obtain and maintain a Top Secret clearance
- Ability to obtain Security+ certification within the first 90 days of employment
Highly preferred:
- Experience with ML model serving and inference platforms such as Triton Inference Server, KServe, Ray Serve, vLLM, or similar technologies
- Experience with secure and compliant deployment practices in regulated or government environments
- Experience with Kubernetes-based ML platforms such as Kubeflow
- Familiarity with service mesh technologies such as Istio
- Experience provisioning and debugging complex CI/CD systems
- Experience with infrastructure as code tools such as Terraform
- Familiarity with software supply chain security, container hardening, vulnerability management, and runtime scanning
- Experience supporting ML systems across multiple deployment environments, including cloud, on-prem, and edge
- Background working with machine learning engineers on model training, evaluation, packaging, and release workflows
- Familiarity with storage and artifact systems used in ML platforms, such as S3-compatible object stores, registries, and metadata/catalog system
What success looks like:
- You help Raft stand up a more mature and repeatable ML platform for deploying and managing models in production
- ML engineers can move faster because deployment, serving, and platform workflows are clearer, more reliable, and easier to use
- Model deployments become more secure, observable, and supportable across real-world mission environments
- The organization gains stronger infrastructure for model lifecycle management, including deployment standards, runtime patterns, and platform ownership
Clearance Requirements:
- Ability to obtain and maintain a Top Secret clearance
Work Type:
- Remote in DMV; McLean, VA; Boston, MA; San Antonio, TX; Colorado Springs, CO; Tampa, FL; Honolulu, HI Locations ONLY
- May require up to 40% travel
Salary Range: $150,000.00 - $200,000.00
What we will offer you:
- Highly competitive salary
- Fully covered healthcare, dental, and vision coverage
- 401(k) and company match
- Take as you need PTO + 11 paid holidays
- Education & training benefits
- Annual budget for your tech/gadgets needs
- Monthly box of yummy snacks to eat while doing meaningful work
- Remote, hybrid, and flexible work options
- Team off-site in fun places!
- Generous Referral Bonuses
- And More!
Our Vision Statement:
We bridge the gap between humans and data through radical transparency and our obsession with the mission.
Our Customer Obsession:
We will approach every deliverable like it's a product. We will adopt a customer-obsessed mentality. As we grow, and our footprint becomes larger, teams and employees will treat each other not only as teammates but customers. We must live the customer-obsessed mindset, always. This will help us scale and it will translate to the interactions that our Rafters have with their clients and other product teams that they integrate with. Our culture will enable our success and set us apart from other companies.
How do we get there?
Public-sector modernization is critical for us to live in a better world. We, at Raft, want to innovate and solve complex problems. And, if we are successful, our generation and the ones that follow us will live in a delightful, efficient, and accessible world where out-of-box thinking, and collaboration is a norm.
Raft’s core philosophy is Ubuntu: I Am, Because We are. We support our “nadi” by elevating the other Rafters. We work as a hyper collaborative team where each team member brings a unique perspective, adding value that did not exist before. People make Raft special. We celebrate each other and our cognitive and cultural diversity. We are devoted to our practice of innovation and collaboration.
We’re an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.
Ready to apply?
Apply to Raft Company WebsitePrincipal MLOps Engineer
Share this job
This is a U.S. based position. All of the programs we support require U.S. citizenship to be eligible for employment. All work must be conducted within the continental U.S.
Who we are:
Raft (https://TeamRaft.com) is a customer-obsessed non-traditional defense tech company dedicated to empowering U.S. military and government agencies with cutting-edge AI/ML and data solutions. We are a leader in autonomous data fusion and Agentic AI, with a purposeful focus on Distributed Data Systems, Platforms at Scale, and Complex Application Development. With headquarters in McLean, VA, our range of clients includes innovative federal and public agencies leveraging design thinking, cutting-edge tech stack, and cloud-native ecosystem. We build digital solutions that impact the lives of millions of Americans.
We’re looking for an experienced Principal ML Ops Engineer to support our customers and join our passionate team of high-impact problem solvers.
About the role:
Raft is building mission-critical AI and data platforms for the Department of Defense (DoD). Our systems ingest and process massive volumes of real-time data from hundreds of sensors and operational sources, transform that data into usable intelligence, and deliver it to operators through mission applications and common operational pictures that support time-sensitive decision-making.
Our platform operates at scale, processing billions of events per day with low-latency data pipelines and cloud-native infrastructure. As Raft expands its AI capabilities, we are investing in a more mature end-to-end machine learning platform to support model development, evaluation, deployment, monitoring, and lifecycle management across both cloud and constrained operational environments.
In this role, you will help design, deploy, and mature Raft’s ML platform and MLOps infrastructure. You will work across Kubernetes-based deployment environments, GPU-enabled infrastructure, model serving systems, CI/CD pipelines, and secure production operations to enable rapid and reliable delivery of machine learning capabilities. This role is ideal for someone who understands both the infrastructure needed to run ML systems in production and the practical needs of ML engineers building and deploying models.
What you’ll do:
- Design, build, and maintain secure, scalable MLOps infrastructure and deployment pipelines for production ML systems
- Help mature Raft’s internal ML platform and model lifecycle capabilities, including model packaging, registry/catalog workflows, deployment, monitoring, and operational support
- Deploy and manage machine learning workloads on Kubernetes, including GPU-enabled clusters
- Support model serving and inference infrastructure for a range of ML use cases, including traditional ML, computer vision, speech/audio, and LLM-based systems
- Build and maintain CI/CD workflows for ML services, model artifacts, and platform components
- Partner closely with ML engineers, software engineers, and product teams to move models from experimentation to reliable operational deployment
- Improve observability, reliability, security, and maintainability across ML infrastructure and services
- Help evaluate and standardize runtime patterns, serving frameworks, and deployment architectures for production ML workloads
- Contribute to infrastructure decisions across edge, on-prem, and cloud-hosted deployment environments
- Support compliance-driven deployment practices and secure software supply chain requirements in defense environments
- Get hands-on with customers at the most forward-leaning places in the Department of War
What we are looking for:
- 7+ years of relevant hands-on experience in software engineering, platform engineering, DevOps, MLOps, or related technical roles
- 5+ years of experience with Docker and Kubernetes in production environments
- 5+ years of experience supporting enterprise cloud infrastructure or applications in AWS, Azure, or similar environments
- Strong experience provisioning, operating, and troubleshooting Kubernetes clusters in production
- Experience building and maintaining machine learning platforms, infrastructure, or pipelines used by engineering or data science teams
- Practical experience deploying machine learning workloads on Kubernetes
- Experience managing clusters or workloads that use GPUs
- Strong understanding of Helm and Kubernetes deployment patterns
- Strong scripting or programming skills, preferably in Python
- Experience with modern software engineering practices including Git, CI/CD, DevOps, and Agile/Scrum workflows
- Strong troubleshooting, systems thinking, and communication skills
- Ability to work independently and collaboratively in a fast-moving environment
- Ability to obtain and maintain a Top Secret clearance
- Ability to obtain Security+ certification within the first 90 days of employment
Highly preferred:
- Experience with ML model serving and inference platforms such as Triton Inference Server, KServe, Ray Serve, vLLM, or similar technologies
- Experience with secure and compliant deployment practices in regulated or government environments
- Experience with Kubernetes-based ML platforms such as Kubeflow
- Familiarity with service mesh technologies such as Istio
- Experience provisioning and debugging complex CI/CD systems
- Experience with infrastructure as code tools such as Terraform
- Familiarity with software supply chain security, container hardening, vulnerability management, and runtime scanning
- Experience supporting ML systems across multiple deployment environments, including cloud, on-prem, and edge
- Background working with machine learning engineers on model training, evaluation, packaging, and release workflows
- Familiarity with storage and artifact systems used in ML platforms, such as S3-compatible object stores, registries, and metadata/catalog system
What success looks like:
- You help Raft stand up a more mature and repeatable ML platform for deploying and managing models in production
- ML engineers can move faster because deployment, serving, and platform workflows are clearer, more reliable, and easier to use
- Model deployments become more secure, observable, and supportable across real-world mission environments
- The organization gains stronger infrastructure for model lifecycle management, including deployment standards, runtime patterns, and platform ownership
Clearance Requirements:
- Ability to obtain and maintain a Top Secret clearance
Work Type:
- Remote in DMV; McLean, VA; Boston, MA; San Antonio, TX; Colorado Springs, CO; Tampa, FL; Honolulu, HI Locations ONLY
- May require up to 40% travel
Salary Range: $150,000.00 - $200,000.00
What we will offer you:
- Highly competitive salary
- Fully covered healthcare, dental, and vision coverage
- 401(k) and company match
- Take as you need PTO + 11 paid holidays
- Education & training benefits
- Annual budget for your tech/gadgets needs
- Monthly box of yummy snacks to eat while doing meaningful work
- Remote, hybrid, and flexible work options
- Team off-site in fun places!
- Generous Referral Bonuses
- And More!
Our Vision Statement:
We bridge the gap between humans and data through radical transparency and our obsession with the mission.
Our Customer Obsession:
We will approach every deliverable like it's a product. We will adopt a customer-obsessed mentality. As we grow, and our footprint becomes larger, teams and employees will treat each other not only as teammates but customers. We must live the customer-obsessed mindset, always. This will help us scale and it will translate to the interactions that our Rafters have with their clients and other product teams that they integrate with. Our culture will enable our success and set us apart from other companies.
How do we get there?
Public-sector modernization is critical for us to live in a better world. We, at Raft, want to innovate and solve complex problems. And, if we are successful, our generation and the ones that follow us will live in a delightful, efficient, and accessible world where out-of-box thinking, and collaboration is a norm.
Raft’s core philosophy is Ubuntu: I Am, Because We are. We support our “nadi” by elevating the other Rafters. We work as a hyper collaborative team where each team member brings a unique perspective, adding value that did not exist before. People make Raft special. We celebrate each other and our cognitive and cultural diversity. We are devoted to our practice of innovation and collaboration.
We’re an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.
Ready to apply?
Apply to Raft Company Website
Senior DevOps Engineer (Active Secret Clearance)
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Build, Deploy, and Maintain AI for an Unpredictable World
Striveworks helps organizations harness the power of artificial intelligence to solve real-world national security and business challenges by serving as the command center between data, models, and business outcomes. Founded by data scientists and engineers, Striveworks set out to make the journey from deployment to ongoing optimization simple and effective.
With Striveworks, organizations aren’t just deploying AI—they’re building systems that remain reliable, adaptable, and ready to scale in an unpredictable world. Mission-critical operations require models that perform where they’re deployed, scale as workloads grow, and adapt rapidly as AI capabilities advance. Striveworks meets these demands, increasing reliability and performance while lowering costs—and enabling confident, data-driven decision-making in dynamic environments.
The Role
As a Senior DevOps Engineer at Striveworks, you will be challenged—and trusted—on day one to take ownership of specific product deployments by maintaining, optimizing, and enhancing our on-premises and cloud computing environments. You will play a crucial role in the successful deployment of our software solutions to clients. You will be responsible for executing technical aspects of implementation projects and for ensuring the seamless integration, customization, and configuration of our software. You will be responsible for maintaining Striveworks’ software deployments using Infrastructure-as-Code (IaC) methodologies. Your expertise will play a critical role for the company as we deploy new instances of Striveworks’ AI operations (AIOps) capabilities to customer infrastructure.
You are right for this opportunity if you value and possess technical expertise and you enjoy pushing the boundaries of your capabilities.
Your day-to-day will include:
- Automating IaC to manage virtual machines and deploy containers, services, and other infrastructure; applying your expertise to deploy custom Kubernetes clusters in AWS, Azure, GCP, on-premises, or hybrid cloud environments
- Working with platform developers, other DevOps teammates, and customer-facing teams to define requirements and build solutions for customer use cases of the platform
- Software deployments to commercial and, later, unclassified, CUI, and classified Department of Defense (DOD) networks
- Incident response and initial triage of critical system faults
The Senior DevOps Engineer works on the DevOps team. You will be responsible for monitoring, automating, and improving software reliability, performance, and availability for various projects. You will also act as a liaison between platform developers and customer-facing teams, taking on operational tasks to ensure the efficient functioning of Striveworks’ solutions. You will work alongside a team of software engineers and data scientists to help them deploy and operate their work as functional products, learning from them so that building effective AI solutions becomes second nature. You might provide guidance and leadership to junior DevOps team members.
You will directly contribute to the success of mission-critical systems within national security and commercial clients. You will be expected to wear multiple hats and to step into vacuums where improvements are needed, and you will be given the breadth to explore new technologies and solutions.
This position offers a hybrid/on-site work environment at customer sites at Schofield Barracks in Oߵahu, Hawaiߵi. You will be expected to travel up to 30% of the time, including some international travel.
The Right Fit
In addition to the specific skills and expertise detailed below, we are looking for individuals who share our values. Sharing a set of values allows us to move at the speed of trust.
Collectively, we value a high-trust work environment where people respect each other and use candor kindly and constructively. We value work that intersects passion and perseverance, we geek out about the potential of our contributions, and we find joy in working hard on things that matter. Finally, we value taking ownership, having agency, and feeling individual responsibility for collective results.
Here’s what we’re looking for:
- 6+ years of direct, hands-on experience in:
- Python and/or Golang programming or other general-purpose programming languages
- Microservice deployment in Kubernetes
- Diagnosing and resolving issues within containerized environments
- Helm Chart and Kustomizations development/deployment
- Automation and IaC (e.g., Terraform, Ansible)
- Cloud infrastructure (e.g., AWS, Azure, GCP, or OpenStack)
- Managing and troubleshooting Linux systems (e.g., RHEL, Ubuntu, CentOS)
- The ability to work cross functionally to define requirements and build solutions for customer use cases of the platform
- The ability to respond professionally and competently to incident reports and triage critical system faults in environments where customers are present
- Active Secret (or above) US security clearance
- Due to the nature of this role, candidates must have US citizenship
The Wish List
We are very interested in candidates who possess the above qualifications, and we appreciate and consider the addition of:
- Experience with DOD networking, tools, infrastructure, security requirements, and policies
- Proficiency with US federal information system security policies, including Security Technical Implementation Guides (STIGs), NIST SP 800-171, NIST SP 800-53, CMMC, and ICD 503
- Experience with software deployments to on-premises and cloud-based unclassified, CUI, and classified networks within the DOD
- Experience with DevSecOps/DevOps and CI/CD for the administration and deployment of GPU-enabled servers
- Experience deploying or maintaining Cloud Native Computing Foundation (CNCF) projects
- Experience with network-attached storage (NAS) and storage area network (SAN) technologies
- Experience with Kubernetes and cloud-native applications and services in denied, disrupted, intermittent, and limited (DDIL) impact environments
The anticipated base pay range for this position is $200,000 to $250,000/year. Striveworks’ total compensation package includes a competitive base salary, equity grants, and cash bonuses.
The Benefits
- Medical/dental/vision insurance
- Voluntary life, long-term disability, accident, and hospital indemnity insurance
- HSA and FSA (including dependent care FSA) plans
- 401(k) plan
- Unlimited PTO
- Paid parental leave
Check us out on Built In!
Striveworks is an Equal Opportunity Employer and does not discriminate in employment on the basis of race, color, religion, belief, sex (including pregnancy and gender identity or expression), national origin, social or ethnic origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non-merit factors. Striveworks will not tolerate discrimination or harassment of any kind.
If you require assistance or a reasonable accommodation in the application process, please contact Operations at hr@striveworks.us.
In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete an employment eligibility verification form upon hire.
Striveworks is a participating employer in the E-Verify program.
Ready to apply?
Apply to Striveworks