We are seeking a skilled Full-Stack Developer to join our team in San Antonio. The ideal candidate will have experience in both front-end and back-end development, capable of designing, developing, and maintaining robust applications. This role involves working on server-side logic, database management, integrating third-party services, and creating seamless and efficient user interfaces. 

What you’ll do:

• Design, develop, and maintain both front-end and back-end components of web applications
• Planning and implementing modifications to Graphic Use Interfaces (GUIs)
• Create technical design drawings, mockups, wireframes, and other associated documentation for PMO and stakeholder review
• Implement and manage server-side logic using programming languages such as Java, Python, Node.js, or Ruby
• Develop and maintain RESTful APIs and web services for seamless integration with front-end components
• Conduct code reviews and provide constructive feedback to team members
• Participate in the entire software development lifecycle, from requirement analysis to deployment and maintenance
• Monitor system performance and implement necessary improvements to ensure high availability and reliability
• Collaborate with DevOps teams to streamline CI/CD processes and automate deployment pipelines
• Develop and maintain and/or assist with technical documentation for systems and processes
• Stay updated with the latest trends and technologies in full-stack development and apply them to improve existing processes

What you’ll need:

• Experience in front-end frameworks such as: React, Angular, or Vue.js. 
• Experience in one or more server-side programming languages such as: Java, Python, Node.js. 
• Experience with one or more database management systems such as: PostgreSQL, MongoDB, Accumulo, or Hadoop
• Experience with containerization using Docker and management of Linux (RHEL) systems

Bonus Points if you have:

• Bachelor’s degree in a technical field
• Previous experience as a Full-Stack Developer or similar position
• Knowledge of RESTful API design and development 
• Experience with Elasticsearch for search functionalities 
• Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) for full-stack development
• Familiarity with additional container orchestration technologies like Kubernetes
• Understanding of security best practices in web development
• Knowledge of DevOps practices and tools such as Gitlab, CI/CD pipelines, and Infrastructure as Code (IaC)
• Excellent problem-solving skills and attention to detail
•  Strong communication and collaboration skills

 Clearance: 

Must have an active Top Secret clearance

Role

This position is for a systems administrator that enjoys building hardware-based operational platforms using internal and external products to include Linux OS images, Kubernetes cluster deployment, and logging systems. As a software engineer, you will be responsible for deploying OS images to hardware, managing an RKE2 multi-node Kubernetes cluster, managing additional containers, network policies, and other Kubernetes Custom Resource Definitions to the cluster, and initial monitoring and maintenance of the cluster. As the systems administrator, on-site support is expected.

Responsibilities

• Participate and lead design and architecture of back-end systems
• Deploy and maintain a robust and high-quality platform, putting the user’s requirements first and always driving towards a working product on-time
• Limit and resource test the platform
• Facilitate delivery and deployment of the platform

Required Qualifications

• Must be able to obtain and maintain a TS/SCI security clearance (only US Citizens are eligible for security clearances).
• Bachelor's degree in Computer Engineering, Computer Science, Software Engineering, or a related technical discipline. In the absence of one of the aforementioned degrees, this requirement can be met with four years of hands-on experience in a Software Engineering or similar full-time position.
• A strong desire to respond to and meet user needs, exemplified by listening, documenting, disseminating, and prioritizing user needs over "nice to haves."
• Willingness to ask questions and stay engaged with team members when tasks are unclear or blockers are encountered.
• Ability to identify necessary tasks, communicate those to the broader team for feedback, and then largely execute independently.
• Trustworthy and able to adapt when project requirements change.
• Able and willing to contribute to the design process for new software features and capabilities.
• Knowledge, expertise, and proficiency with one or more common, general purpose programming languages (Go, Python, C, Rust, JavaScript, etc.). Being language agnostic is a plus (i.e. picking the right tool for the job, not just picking one tool for all jobs).
• Able to set up and maintain one's own development system (e.g., Ubuntu VM) in a cloud-based platform, including personalized IDE settings, access keys, system package updates, etc.
• Familiar and comfortable working with containers, including creating, deploying, and debugging custom images with common tools (Docker, Podman, etc.).
• Familiarity with cloud-based computing resources (e.g., AWS, Azure).
• Knowledge of security concepts, networks, and system internals to use on a daily basis.
• Ability to work with and troubleshoot real hardware of varying types (network switches, servers, routers, hubs, etc.).
• Proficient in Linux-based development environments (e.g., Debian- or RedHat-based distributions).
• Proficient with version control software (e.g., Git) and repository hosting tools (e.g., GitLab).
• Willingness and ability to travel up to 15% of the year, including both travel that is local to the DC, Maryland, Virginia (DMV) area and travel to multiple sites in the United States.

Preferred Qualifications (in addition to the required qualifications)

• Current US TS/SCI security clearance
• 2 years of industry experience in a platform engineering, DevOps or similar role in the Cyber Operation Domain
• Experience communicating with customers and end-users

Accenture Federal Services (AFS) brings together commercial innovation with the latest technology to deliver bold solutions for federal missions. We help our clients modernize systems, improve operations, and enhance the citizen experience. Join us and help drive meaningful impact at scale.

The Work:

As a Business Analyst, you will support mission‑driven technology initiatives by analyzing current business processes, gathering and documenting requirements, and translating those needs into clear, actionable user stories for technical teams. You will collaborate closely with stakeholders, facilitate discussions, and support the full systems development lifecycle to ensure solutions meet business, functional, and compliance requirements.

You will:

• Lead and support requirements elicitation, discovery sessions, and workflow analysis to understand current‑state systems, data, and processes.
• Define future‑state business processes, business rules, and user journeys; perform gap analysis and document findings.
• Develop business, functional, and system requirements, translating them into user stories and acceptance criteria for Agile teams.
• Create process diagrams, data mapping artifacts, and functional specifications to support design and development activities.
• Partner with architects, developers, and testers to clarify requirements, support backlog refinement, and participate in sprint activities.
• Facilitate stakeholder communication, ensure alignment on requirements, and document key decisions throughout the project lifecycle.

What You Need:

• Experience supporting the SDLC and Agile delivery environments (Scrum, Kanban).
• Demonstrated ability to document business processes, requirements, user stories, and acceptance criteria.
• Experience with Jira, Azure DevOps, Confluence, and/or similar collaboration and work‑tracking tools.
• Ability to perform SQL queries (read/joins/basic analysis).

Bonus Points:

• Experience supporting federal programs or mission‑oriented environments.
• Background in cloud/web modernization (AWS/Azure/GCP)
• Experience supporting testing, QA, automation tools, or user‑facing training materials.
• Experience with tools such as Visio/Lucidchart, Power BI/Tableau, or Medallia (for CX programs)

Eligibility Requirements:

• U.S. citizenship required
• Active Public Trust or the ability to obtain one

Location:

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. 

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. 

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. 

EMPLOYER IS A CONTRACTOR FOR THE U.S. GOVERNMENT. THIS POSITION WILL REQUIRE U.S. CITIZENSHIP.

Role Description: 

We are seeking a talented and experienced Platform Engineer to join our team in a hybrid capacity in San Antonio, Texas. Possessing strong proficiency with Kubernetes, the ideal candidate will play a crucial role in the development and maintenance of our platform, demonstrating a strong understanding of system architecture, problem-solving skills, and the ability to guide junior engineers.

As a Platform Engineer within our organization, you will join a team of dedicated unicorns who are focused on advancing freedom and independence globally. Our teams work on various different technical baselines depending on specific engagements. We focus our Products on the Platform layer, but to deliver for our Heroes, we also work IaC automation, security, and implementation.

Responsibilities: 

You will help us automate and build a runtime Production Environment and serve as a link between the Applications, either custom development, COTS, or OSS, and that environment, advocating best practices and facilitating communication between the application teams and platform teams.

In this position, you will be expected to: 

• Validate Solutions/Implementations: Ensure that solutions and implementations align with the outlined tasks and business requirements. Conduct thorough validations to maintain the integrity and efficiency of the platform.
• Independently Problem Solve: Demonstrate the ability to identify and solve business problems independently. Develop small components to address specific challenges without relying on explicit architecture diagrams.
• Understand Medium-Level Tasking: Comprehend how medium-level tasks contribute to the achievement of overall goals. Collaborate with cross-functional teams to integrate various components into a cohesive and functional platform.
• Estimate Time and Effort: Provide accurate time and effort estimates for medium-sized tasks. Assist in project planning and resource allocation based on estimated timelines.
• Demonstrate Programming Language Proficiency: Possess familiarity with at least one programming language. Exhibit a basic understanding of when to use a programming language versus a shell for efficient task execution.
• Own the bridge between the Application Development team(s) and the Production Environment

Travel Expectations: 10%-25%

The listed responsibilities are not exhaustive and additional responsibilities may be assigned based on the evolving needs of the organization. We are seeking a dynamic individual who is able to adapt and take on new responsibilities as they arise. 

Preferred Experience and Qualifications:

• Proven experience as a Platform Engineer or similar role, with a focus on system architecture and development.
• Demonstrated experience with cloud-native technologies such as Kubernetes, Google Cloud, and Docker.
• Familiarity with continuous delivery, distributed architectures, systems, everything-as-code, containerization, and cloud services.
• Proficiency in at least one programming language (e.g., Python, Go, Ansible) and a basic understanding of shell scripting.
• Proficient with YAML.
• Experienced in working on a team following an Agile framework in a remote environment.
• Strong problem-solving skills and the ability to work independently.
• Excellent communication skills and the ability to collaborate effectively with cross-functional teams.
• Experience with security automation and familiarity with API Security, Container Security, and Cloud Security.
• Familiar with architecture security design, monitoring, and performance instrumentation in a complex enterprise environment.
• Comfort with debugging systems and reading/writing code.
• Hold a security clearance/Eligible to apply for a security clearance.
• Possess a DoD 8570 IAT II certification.
• Experienced in Department of Defense work, specifically working on a production Authority to Operate (ATO'd) system.
• Knowledgeable about DevSecOps/DevOps and CI/CD theory.

Description

Captivation Software is seeking a highly motivated and experienced DevOps Engineer to join our fast-paced development team. The ideal candidate will have strong working knowledge in Linux systems administration, and a background in Big Data solutions, configuration management, automation, scripting, and AWS. The DevOps Engineer will be responsible for implementing infrastructure, automating deployment processes, and ensuring the reliability and scalability of our services. Work is performed mostly on customer site in San Antonio, TX 5 days/week. 

If you have a passion for DevOps and are interested in working with a dynamic and innovative team, we encourage you to apply for this exciting opportunity.

Responsibilities

• Support development and deployment of cloud infrastructure in AWS
• Support development and deployment of non-cloud (Edge) infrastructure of on-premise and portable equipment
• Automate deployment processes and ensure reliability and scalability of services
• Manage and maintain Kubernetes containers and cloud infrastructure on AWS
• Collaborate with development teams to integrate their applications into the infrastructure
• Monitor and troubleshoot production systems and resolve issues as necessary
• Continuously improve processes and tools to ensure high availability and performance
• Stay current with new technologies and industry trends, continuously exploring new ways to improve our infrastructure
• Other duties as assigned

Requirements

Security Clearance:

• A current TS/SCI U.S. Government Security clearance is required; U.S. citizenship required. 

Minimum Qualifications:

• 5+ years of experience in DevOps Engineering or Software Development (Java preferred) and Bachelors in related field; or 3 years relevant experience with Masters in related field; or High School Diploma or equivalent and 9 years relevant experience.
• Strong knowledge of Linux, including system administration and troubleshooting
• Proficient in configuration management tools such as Ansible or Puppet
• Knowledge of AWS services (EC2, S3, Lambda) and their application to deployment and management of infrastructure
• Experience with application and OS deployment, scaling, and management
• Ability to develop in multiple programming languages such as bash, Python, or Go
• Familiarity with Git and other development tools such as deployment pipelines
• Excellent problem-solving skills and the ability to identify and troubleshoot complex issues
• Excellent oral and written communication skills.
• Understanding of AGILE software development methodologies and use of standard software development tool suites
• Must be able to obtain Security+ certification within 60 days of hire.
• Must be able to work on-site daily at the customer location in San Antonio, TX, with occasional opportunities to be working from home. Flexibility is essential to accommodate schedule changes based on customer and team needs.

Preferred Qualifications:

• Experience with big data technologies like: Hadoop, Spark, PostgreSQL, ElasticSearch, Hive, Drill, Impala, Trino, Presto, etc.
• Experience with containers EKS, Diode, CI/CD, and Terraform are a plus
• Work could possibly require some on-call work. 

This position is open for direct hires only. We will not consider candidates from third party staffing/recruiting firms.