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

Role Description: 

We are seeking an IT Engineer to join our team, based primarily out of our San Antonio, TX office. This role is first and foremost a hardware role, the primary owner of physical infrastructure at Defense Unicorns' San Antonio location, responsible for racking servers, configuring switching and network gear, and maintaining a growing lab environment that supports active defense programs. When not heads-down on hardware, this person is a contributor to day-to-day IT operations, handling helpdesk tickets, endpoint support, and IT projects alongside the broader IT OPS team. The ideal candidate thrives in a hands-on lab environment, has real experience standing up physical infrastructure, and can context-switch into IT OPS work without losing momentum. This is an onsite role; physical presence is the job.

Responsibilities: 

Hardware & Infrastructure (~70%)

• Install, configure, and maintain servers, rack-mount switches, and associated network infrastructure in the San Antonio office and lab environments
• Stand up and maintain virtualization environments on IT-owned bare-metal hardware
• Lead rack layout, cable management, patch panel termination, and physical infrastructure documentation
• Support UPS and PDU installation, configuration, and monitoring
• Configure and maintain network infrastructure including switches, access points, and security appliances
• Lead hardware procurement coordination, maintain physical and digital asset inventory, and support engineering and delivery teams with hardware staging needs
• Assist with edge and lab hardware as needed, including mini PCs, single-board computers, and portable networking gear
• Support physical security infrastructure as needed, including access control and related CMMC-adjacent hardware considerations

IT Operations (~30%)

• Provide Tier 1 and Tier 2 helpdesk support, triaging and resolving tickets or escalating as appropriate
• Administer MDM (Jamf) for device enrollment, policy enforcement, and compliance reporting
• Support endpoint hardware management (primarily macOS) alongside other IT team members, including imaging, configuration, deployment, and decommission
• Support user onboarding and offboarding workflows including access provisioning and equipment movement
• Manage access through Google Admin Console and related identity tools
• Collaborate with third-party vendors and internal stakeholders on SaaS tool rollouts, troubleshooting, and updates
• Contribute to IT projects, process improvements, and compliance initiatives aligned with NIST SP 800-171 and CMMC

Travel Expectations/Requirements: Primarily onsite in San Antonio; occasional travel to other Defense Unicorns locations (~20%)

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. 

Minimum Experience and Qualifications

• 3+ years in an IT operations, systems administration, or infrastructure role
• Hands-on experience racking and configuring servers and network switches in a lab or data center environment
• Experience with virtualization platforms on IT-managed infrastructure (Proxmox, ESXi, or similar)
• Demonstrated homelab or lab environment experience, comfortable standing up and troubleshooting infrastructure from scratch
• Familiarity with structured cabling, patch panel termination, and physical infrastructure documentation
• Experience with layer 2/3 networking concepts (VLANs, switching, routing)
• Experience with change management processes and IT documentation practices
• Experience with helpdesk or trouble ticketing systems
• Familiarity with macOS endpoint management and MDM solutions (Jamf preferred)
• Experience with Google Admin Console or similar directory/identity management tools
• US citizenship required; must be eligible for CUI access
• Ability to work independently in an onsite environment and manage competing priorities without close supervision

Preferred Experience and Qualifications:

• Experience with enterprise rack-mount server configuration and out-of-band management (e.g., iDRAC, iLO, IPMI)
• Experience with managed switching and prosumer/enterprise network stacks (e.g., UniFi, Cisco, Ubiquiti, or similar)
• Experience in a defense contractor, government, or classified lab environment
• Familiarity with NIST SP 800-171, CMMC 2.0, or similar compliance frameworks
• Exposure to edge compute platforms (single-board computers, mini PCs, GPU workstations)
• Experience contributing to endpoint hardware programs in a shared-ownership model

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. 

Overview

Join us to work collaboratively with our talented team of dynamic and passionate engineers to deliver capabilities that enable our customers to make a difference. You'll deploy and operate ArcGIS Velocity and ArcGIS Workflow Manager SaaS solutions. You will also have the opportunity to design, deploy, and operate next-generation real-time and big data GIS software-as-a-service (SaaS) capabilities for thousands of cloud users worldwide.

Our teams have a broad mix of experience levels and tenures that support an environment which promotes professional development. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future. Our team also puts a high value on work-life balance, and we understand that striking a healthy balance between your personal and professional life is crucial to your happiness and success here. We offer a flexible hybrid schedule so you can have a more productive and well-balanced life both in and outside of work.

The Professional Services division is the consulting and implementation arm of Esri. We break ground in new markets, push the technology envelope and ultimately deliver transformational solutions to high profile clients worldwide. The Professional Services organization is comprised of nearly 1,000 talented business and technical professionals who strive every day to help our users be successful. This product team works closely with solution delivery consultants to envision and then ‘make real’ the emerging requirements in industry, government, and other user communities.

Responsibilities

• Collaborate with a team of SRE engineers to operate SaaS capabilities across multiple regions on the cloud platform
• Design, implement, configure, and utilize monitoring systems to monitor the health of SaaS products
• Manage infrastructure used for ArcGIS Velocity and ArcGIS Workflow Manager, respond to alerts, and troubleshoot problems to resolution
• Develop, implement, and maintain automation solutions for repetitive operational tasks, such as deployment pipelines, incident resolution, and scaling processes
• Design and implement the deployment and upgrade containerized micro-service components that, when combined, power Esri’s SaaS offerings
• Create and automate Git workflows to simplify code integration, testing, and infrastructure deployments
• Participate in technical spike efforts, bringing new innovative ideas to future versions of our software
• Troubleshoot the system incidents and provide root cause analysis reports
• Provide rotational on-call technical support

Requirements

• 5+ years of experience managing Kubernetes (EKS), logging and monitoring (ELK, Prometheus), and container technologies (Docker, ECS)
• Proficient in using Terraform for automating infrastructure provisioning and management
• Ability to design and automate Git workflows for streamlined code integration, testing, and infrastructure deployment
• Ability to write scripts to deploy infrastructure and/or applications (Bash, Python, Terraform)
• High level of understanding and experience with cloud computing platforms (AWS)
• Strong knowledge of Linux Operating system administration, including troubleshooting, performance tuning, and shell scripting
• Proficient in cloud networking, including VPCs, subnets, security groups, and VPNs in platforms like AWS
• Skilled in identifying and resolving system and application issues through effective troubleshooting and root cause analysis
• Working knowledge of a source control and issue management system, preferably GitHub
• Working knowledge of authoring, deploying, and troubleshooting Java applications on AWS Lambda
• Bachelor’s degree in computer science, computer engineering, GIS, or information systems

Recommended Qualifications

• 5+ years of experience designing, administering, and/or maintaining cloud environments, such as AWS, supporting 24×7 high-availability production environments
• Interest in working with GitOps principles to automate the deployment of applications on Kubernetes clusters
• Certifications: AWS Certified Solution Architect Associate, CKA/CKAD or similar
• Experience managing OpenSearch (datastore or logstore), and Kafka for managing distributed data streams and ensuring high availability in large-scale systems
• Ability to work with continuous integration and delivery best practices
• Knowledge of operating resilient, highly available, scalable, and performance SaaS capabilities
• Knowledge of Esri ArcGIS or other web mapping technologies
• Master’s degree in computer science, computer engineering, GIS, or information systems

#LI-DR5

Overview

Join us to work collaboratively with our talented team of dynamic and passionate engineers to deliver capabilities that enable our customers to make a difference. You'll deploy and operate ArcGIS Velocity and ArcGIS Workflow Manager SaaS solutions. You will also have the opportunity to design, deploy, and operate next-generation real-time and big data GIS software-as-a-service (SaaS) capabilities for thousands of cloud users worldwide.

Our teams have a broad mix of experience levels and tenures that support an environment which promotes professional development. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future. Our team also puts a high value on work-life balance, and we understand that striking a healthy balance between your personal and professional life is crucial to your happiness and success here. We offer a flexible hybrid schedule so you can have a more productive and well-balanced life both in and outside of work.

The Professional Services division is the consulting and implementation arm of Esri. We break ground in new markets, push the technology envelope and ultimately deliver transformational solutions to high profile clients worldwide. The Professional Services organization is comprised of nearly 1,000 talented business and technical professionals who strive every day to help our users be successful. This product team works closely with solution delivery consultants to envision and then ‘make real’ the emerging requirements in industry, government, and other user communities.

Responsibilities

• Collaborate with a team of SRE engineers to operate SaaS capabilities across multiple regions on the cloud platform
• Design, implement, configure, and utilize monitoring systems to monitor the health of SaaS products
• Manage infrastructure used for ArcGIS Velocity and ArcGIS Workflow Manager, respond to alerts, and troubleshoot problems to resolution
• Develop, implement, and maintain automation solutions for repetitive operational tasks, such as deployment pipelines, incident resolution, and scaling processes
• Design and implement the deployment and upgrade containerized micro-service components that, when combined, power Esri’s SaaS offerings
• Create and automate Git workflows to simplify code integration, testing, and infrastructure deployments
• Participate in technical spike efforts, bringing new innovative ideas to future versions of our software
• Troubleshoot the system incidents and provide root cause analysis reports
• Provide rotational on-call technical support

Requirements

• 5+ years of experience managing Kubernetes (EKS), logging and monitoring (ELK, Prometheus), and container technologies (Docker, ECS)
• Proficient in using Terraform for automating infrastructure provisioning and management
• Ability to design and automate Git workflows for streamlined code integration, testing, and infrastructure deployment
• Ability to write scripts to deploy infrastructure and/or applications (Bash, Python, Terraform)
• High level of understanding and experience with cloud computing platforms (AWS)
• Strong knowledge of Linux Operating system administration, including troubleshooting, performance tuning, and shell scripting
• Proficient in cloud networking, including VPCs, subnets, security groups, and VPNs in platforms like AWS
• Skilled in identifying and resolving system and application issues through effective troubleshooting and root cause analysis
• Working knowledge of a source control and issue management system, preferably GitHub
• Working knowledge of authoring, deploying, and troubleshooting Java applications on AWS Lambda
• Bachelor’s degree in computer science, computer engineering, GIS, or information systems

Recommended Qualifications

• 5+ years of experience designing, administering, and/or maintaining cloud environments, such as AWS, supporting 24×7 high-availability production environments
• Interest in working with GitOps principles to automate the deployment of applications on Kubernetes clusters
• Certifications: AWS Certified Solution Architect Associate, CKA/CKAD or similar
• Experience managing OpenSearch (datastore or logstore), and Kafka for managing distributed data streams and ensuring high availability in large-scale systems
• Ability to work with continuous integration and delivery best practices
• Knowledge of operating resilient, highly available, scalable, and performance SaaS capabilities
• Knowledge of Esri ArcGIS or other web mapping technologies
• Master’s degree in computer science, computer engineering, GIS, or information systems

#LI-DR5

Overview

Join us to work collaboratively with our talented team of dynamic and passionate engineers to deliver capabilities that enable our customers to make a difference. You'll deploy and operate ArcGIS Velocity and ArcGIS Workflow Manager SaaS solutions. You will also have the opportunity to design, deploy, and operate next-generation real-time and big data GIS software-as-a-service (SaaS) capabilities for thousands of cloud users worldwide.

Our teams have a broad mix of experience levels and tenures that support an environment which promotes professional development. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future. Our team also puts a high value on work-life balance, and we understand that striking a healthy balance between your personal and professional life is crucial to your happiness and success here. We offer a flexible hybrid schedule so you can have a more productive and well-balanced life both in and outside of work.

The Professional Services division is the consulting and implementation arm of Esri. We break ground in new markets, push the technology envelope and ultimately deliver transformational solutions to high profile clients worldwide. The Professional Services organization is comprised of nearly 1,000 talented business and technical professionals who strive every day to help our users be successful. This product team works closely with solution delivery consultants to envision and then ‘make real’ the emerging requirements in industry, government, and other user communities.

Responsibilities

• Collaborate with a team of SRE engineers to operate SaaS capabilities across multiple regions on the cloud platform
• Design, implement, configure, and utilize monitoring systems to monitor the health of SaaS products
• Manage infrastructure used for ArcGIS Velocity and ArcGIS Workflow Manager, respond to alerts, and troubleshoot problems to resolution
• Develop, implement, and maintain automation solutions for repetitive operational tasks, such as deployment pipelines, incident resolution, and scaling processes
• Design and implement the deployment and upgrade containerized micro-service components that, when combined, power Esri’s SaaS offerings
• Create and automate Git workflows to simplify code integration, testing, and infrastructure deployments
• Participate in technical spike efforts, bringing new innovative ideas to future versions of our software
• Troubleshoot the system incidents and provide root cause analysis reports
• Provide rotational on-call technical support

Requirements

• 5+ years of experience managing Kubernetes (EKS), logging and monitoring (ELK, Prometheus), and container technologies (Docker, ECS)
• Proficient in using Terraform for automating infrastructure provisioning and management
• Ability to design and automate Git workflows for streamlined code integration, testing, and infrastructure deployment
• Ability to write scripts to deploy infrastructure and/or applications (Bash, Python, Terraform)
• High level of understanding and experience with cloud computing platforms (AWS)
• Strong knowledge of Linux Operating system administration, including troubleshooting, performance tuning, and shell scripting
• Proficient in cloud networking, including VPCs, subnets, security groups, and VPNs in platforms like AWS
• Skilled in identifying and resolving system and application issues through effective troubleshooting and root cause analysis
• Working knowledge of a source control and issue management system, preferably GitHub
• Working knowledge of authoring, deploying, and troubleshooting Java applications on AWS Lambda
• Bachelor’s degree in computer science, computer engineering, GIS, or information systems

Recommended Qualifications

• 5+ years of experience designing, administering, and/or maintaining cloud environments, such as AWS, supporting 24×7 high-availability production environments
• Interest in working with GitOps principles to automate the deployment of applications on Kubernetes clusters
• Certifications: AWS Certified Solution Architect Associate, CKA/CKAD or similar
• Experience managing OpenSearch (datastore or logstore), and Kafka for managing distributed data streams and ensuring high availability in large-scale systems
• Ability to work with continuous integration and delivery best practices
• Knowledge of operating resilient, highly available, scalable, and performance SaaS capabilities
• Knowledge of Esri ArcGIS or other web mapping technologies
• Master’s degree in computer science, computer engineering, GIS, or information systems

#LI-DR5

Overview

Join us to work collaboratively with our talented team of dynamic and passionate engineers to deliver capabilities that enable our customers to make a difference. You'll deploy and operate ArcGIS Velocity and ArcGIS Workflow Manager SaaS solutions. You will also have the opportunity to design, deploy, and operate next-generation real-time and big data GIS software-as-a-service (SaaS) capabilities for thousands of cloud users worldwide.

Our teams have a broad mix of experience levels and tenures that support an environment which promotes professional development. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future. Our team also puts a high value on work-life balance, and we understand that striking a healthy balance between your personal and professional life is crucial to your happiness and success here. We offer a flexible hybrid schedule so you can have a more productive and well-balanced life both in and outside of work.

The Professional Services division is the consulting and implementation arm of Esri. We break ground in new markets, push the technology envelope and ultimately deliver transformational solutions to high profile clients worldwide. The Professional Services organization is comprised of nearly 1,000 talented business and technical professionals who strive every day to help our users be successful. This product team works closely with solution delivery consultants to envision and then ‘make real’ the emerging requirements in industry, government, and other user communities.

Responsibilities

• Collaborate with a team of SRE engineers to operate SaaS capabilities across multiple regions on the cloud platform
• Design, implement, configure, and utilize monitoring systems to monitor the health of SaaS products
• Manage infrastructure used for ArcGIS Velocity and ArcGIS Workflow Manager, respond to alerts, and troubleshoot problems to resolution
• Develop, implement, and maintain automation solutions for repetitive operational tasks, such as deployment pipelines, incident resolution, and scaling processes
• Design and implement the deployment and upgrade containerized micro-service components that, when combined, power Esri’s SaaS offerings
• Create and automate Git workflows to simplify code integration, testing, and infrastructure deployments
• Participate in technical spike efforts, bringing new innovative ideas to future versions of our software
• Troubleshoot the system incidents and provide root cause analysis reports
• Provide rotational on-call technical support

Requirements

• 5+ years of experience managing Kubernetes (EKS), logging and monitoring (ELK, Prometheus), and container technologies (Docker, ECS)
• Proficient in using Terraform for automating infrastructure provisioning and management
• Ability to design and automate Git workflows for streamlined code integration, testing, and infrastructure deployment
• Ability to write scripts to deploy infrastructure and/or applications (Bash, Python, Terraform)
• High level of understanding and experience with cloud computing platforms (AWS)
• Strong knowledge of Linux Operating system administration, including troubleshooting, performance tuning, and shell scripting
• Proficient in cloud networking, including VPCs, subnets, security groups, and VPNs in platforms like AWS
• Skilled in identifying and resolving system and application issues through effective troubleshooting and root cause analysis
• Working knowledge of a source control and issue management system, preferably GitHub
• Working knowledge of authoring, deploying, and troubleshooting Java applications on AWS Lambda
• Bachelor’s degree in computer science, computer engineering, GIS, or information systems

Recommended Qualifications

• 5+ years of experience designing, administering, and/or maintaining cloud environments, such as AWS, supporting 24×7 high-availability production environments
• Interest in working with GitOps principles to automate the deployment of applications on Kubernetes clusters
• Certifications: AWS Certified Solution Architect Associate, CKA/CKAD or similar
• Experience managing OpenSearch (datastore or logstore), and Kafka for managing distributed data streams and ensuring high availability in large-scale systems
• Ability to work with continuous integration and delivery best practices
• Knowledge of operating resilient, highly available, scalable, and performance SaaS capabilities
• Knowledge of Esri ArcGIS or other web mapping technologies
• Master’s degree in computer science, computer engineering, GIS, or information systems

#LI-DR5

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.