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

Cybersecurity Engineer, Senior Manager

Two Six Technologies is seeking a visionary Cybersecurity Engineer, Senior Manager to architect, build, and defend the highly secure environments that power our advanced R&D initiatives. We are looking for a true security architect who can seamlessly bridge the gap between rigorous government security frameworks (NIST, STIGs, CMMC) and complex operational engineering. In this role, you will lead the strategic design of our secure infrastructure, guide DevSecOps integration across software projects, and engineer pragmatic, intent-based security solutions. If you excel at deconflicting stringent compliance mandates with real-world engineering challenges, and thrive in a role that spans infrastructure defense, network architecture, and application security, we want you to lead our team.

Preferable locations are San Antonio TX and Arlington VA. The role is considered hybrid, and would require at least 3 days a week in the office at either location.

Key Responsibilities

• Strategic Security Architecture: Architect custom security solutions that deconflict stringent government compliance requirements with critical operational needs. Move beyond standard "box checking" to design risk-optimized, tailored controls.
• Intent-Based Engineering: Engineer alternative technical solutions when literal remediation causes operational failure. Leverage deep system knowledge and industry best practices to meet the core security intent of a framework while maintaining system functionality.
• Design & Implementation: Lead the hands-on technical development, configuration, and deployment of secure IT infrastructure and custom security tools, ensuring all architectures are defensible during an audit.
• Threat Defense & Mitigation Strategy: Develop high-level strategies, playbooks, and architectures for threat detection and incident response. Oversee the vulnerability mitigation lifecycle, guiding the team's efforts so that day-to-day monitoring is handled by staff while the Lead focuses on proactive, structural defense improvements.
• Collaborative Security: Partner with development and IT teams to seamlessly integrate security and compliance into CI/CD pipelines and software development lifecycles while supporting innovation.
• Team Leadership & Mentorship: Direct a small team of security professionals across multiple projects. Mentor junior team members on how to balance strict compliance auditing with pragmatic, operational engineering solutions.

Required Skills & Qualifications

• Education: Bachelor’s degree in Computer Science, Cybersecurity, Information Security, or comparable experience.
• Leadership: Experience managing small interactive teams.  Candidates will be required to task junior reports, and should have strong mentorship skills.
• Strategic Risk & Compliance Mastery: Deep understanding of NIST 800-171, NIST 800-53b, CMMC, and DISA STIGs. Proven ability to interpret the underlying risk objective of a control to engineer solutions that satisfy auditors without breaking operations.
• Advanced Systems Expertise: Deep technical mastery of operating systems (primarily RHEL/Linux). Must possess the system-level knowledge (e.g., Linux internals, process management) required to design custom, defensible security configurations backed by vendor documentation when standard STIG guidance is insufficient.
• Operational Deconfliction: A highly analytical mindset with a track record of identifying conflicts between security mandates and operational uptime, and successfully architecting "semi-custom" solutions that keep risk to an acceptable minimum.
• Network Security Architecture: Strong architectural understanding of secure network paradigms (e.g., Zero Trust, macro/micro-segmentation) and fundamentals. Ability to guide the implementation of complex boundary defenses and validate network security controls.
• Application Security & Code Analysis: High technical competency in application security principles. Must be capable of analyzing SAST tool outputs, architecting defensible arguments for false positives to present to customers, and providing strategic guidance to developers on resolving legitimate vulnerabilities.
• Security Automation: Strategic approach to automating repetitive security operations using scripting and CI/CD pipelines. Proven ability to build self-sustaining security workflows that free up engineering staff to focus on high-complexity problems.
• Clearance:  Eligibility to obtain and maintain a security clearance up to TS/SCI. 

Preferred Experience

• Advanced Code Review: Practical experience reading, reviewing, and defending SAST findings in compiled languages such as Java, Golang, or C and/or interpreted languages like Python or NodeJS.
• DevSecOps & Containerization: Hands-on experience architecting secure CI/CD pipelines and software development workflows utilizing platforms like Jenkins, GitHub, or GitLab. Familiarity with securing OCI-compliant container ecosystems (e.g., Docker) is highly desirable.
• Virtualization & Cloud Architecture: Experience securing, architecting, or managing hyperconverged virtual infrastructure (specifically VMware or Proxmox) and/or cloud-native enterprise environments (e.g., AWS).
• Enterprise Boundary Defense: Practical experience engineering, deploying, or migrating advanced enterprise firewall and network security solutions (e.g., Fortinet).
• Specialized Enclaves & R&D Networks: Proven experience designing, auditing, or managing compliance for research and development (R&D) environments, specifically involving the creation or maintenance of CMMC Level 2 compliant networks.
• AI Security Oversight: Experience implementing security guardrails for teams using AI-assisted coding tools (e.g., Cursor, GitHub Copilot, Gemini).
• Automated Compliance: Ability to translate security mandates into Policy-as-Code to ensure rapid, AI-generated deployments remain compliant with NIST/CMMC frameworks.
• AI Risk Assessment: Practical understanding of the OWASP Top 10 for LLMs and how to mitigate risks related to prompt injection and AI-generated code vulnerabilities.
• Clearance:  Active TS/SCI clearance

Clearance Requirements:

• This position requires eligibility to obtain and maintain a security clearance up to TS/SCI

#LI-MS1

#Hybrid

Cybersecurity Engineer, Senior Manager

Two Six Technologies is seeking a visionary Cybersecurity Engineer, Senior Manager to architect, build, and defend the highly secure environments that power our advanced R&D initiatives. We are looking for a true security architect who can seamlessly bridge the gap between rigorous government security frameworks (NIST, STIGs, CMMC) and complex operational engineering. In this role, you will lead the strategic design of our secure infrastructure, guide DevSecOps integration across software projects, and engineer pragmatic, intent-based security solutions. If you excel at deconflicting stringent compliance mandates with real-world engineering challenges, and thrive in a role that spans infrastructure defense, network architecture, and application security, we want you to lead our team.

Preferable locations are San Antonio TX and Arlington VA. The role is considered hybrid, and would require at least 3 days a week in the office at either location.

Key Responsibilities

• Strategic Security Architecture: Architect custom security solutions that deconflict stringent government compliance requirements with critical operational needs. Move beyond standard "box checking" to design risk-optimized, tailored controls.
• Intent-Based Engineering: Engineer alternative technical solutions when literal remediation causes operational failure. Leverage deep system knowledge and industry best practices to meet the core security intent of a framework while maintaining system functionality.
• Design & Implementation: Lead the hands-on technical development, configuration, and deployment of secure IT infrastructure and custom security tools, ensuring all architectures are defensible during an audit.
• Threat Defense & Mitigation Strategy: Develop high-level strategies, playbooks, and architectures for threat detection and incident response. Oversee the vulnerability mitigation lifecycle, guiding the team's efforts so that day-to-day monitoring is handled by staff while the Lead focuses on proactive, structural defense improvements.
• Collaborative Security: Partner with development and IT teams to seamlessly integrate security and compliance into CI/CD pipelines and software development lifecycles while supporting innovation.
• Team Leadership & Mentorship: Direct a small team of security professionals across multiple projects. Mentor junior team members on how to balance strict compliance auditing with pragmatic, operational engineering solutions.

Required Skills & Qualifications

• Education: Bachelor’s degree in Computer Science, Cybersecurity, Information Security, or comparable experience.
• Leadership: Experience managing small interactive teams.  Candidates will be required to task junior reports, and should have strong mentorship skills.
• Strategic Risk & Compliance Mastery: Deep understanding of NIST 800-171, NIST 800-53b, CMMC, and DISA STIGs. Proven ability to interpret the underlying risk objective of a control to engineer solutions that satisfy auditors without breaking operations.
• Advanced Systems Expertise: Deep technical mastery of operating systems (primarily RHEL/Linux). Must possess the system-level knowledge (e.g., Linux internals, process management) required to design custom, defensible security configurations backed by vendor documentation when standard STIG guidance is insufficient.
• Operational Deconfliction: A highly analytical mindset with a track record of identifying conflicts between security mandates and operational uptime, and successfully architecting "semi-custom" solutions that keep risk to an acceptable minimum.
• Network Security Architecture: Strong architectural understanding of secure network paradigms (e.g., Zero Trust, macro/micro-segmentation) and fundamentals. Ability to guide the implementation of complex boundary defenses and validate network security controls.
• Application Security & Code Analysis: High technical competency in application security principles. Must be capable of analyzing SAST tool outputs, architecting defensible arguments for false positives to present to customers, and providing strategic guidance to developers on resolving legitimate vulnerabilities.
• Security Automation: Strategic approach to automating repetitive security operations using scripting and CI/CD pipelines. Proven ability to build self-sustaining security workflows that free up engineering staff to focus on high-complexity problems.
• Clearance:  Eligibility to obtain and maintain a security clearance up to TS/SCI. 

Preferred Experience

• Advanced Code Review: Practical experience reading, reviewing, and defending SAST findings in compiled languages such as Java, Golang, or C and/or interpreted languages like Python or NodeJS.
• DevSecOps & Containerization: Hands-on experience architecting secure CI/CD pipelines and software development workflows utilizing platforms like Jenkins, GitHub, or GitLab. Familiarity with securing OCI-compliant container ecosystems (e.g., Docker) is highly desirable.
• Virtualization & Cloud Architecture: Experience securing, architecting, or managing hyperconverged virtual infrastructure (specifically VMware or Proxmox) and/or cloud-native enterprise environments (e.g., AWS).
• Enterprise Boundary Defense: Practical experience engineering, deploying, or migrating advanced enterprise firewall and network security solutions (e.g., Fortinet).
• Specialized Enclaves & R&D Networks: Proven experience designing, auditing, or managing compliance for research and development (R&D) environments, specifically involving the creation or maintenance of CMMC Level 2 compliant networks.
• AI Security Oversight: Experience implementing security guardrails for teams using AI-assisted coding tools (e.g., Cursor, GitHub Copilot, Gemini).
• Automated Compliance: Ability to translate security mandates into Policy-as-Code to ensure rapid, AI-generated deployments remain compliant with NIST/CMMC frameworks.
• AI Risk Assessment: Practical understanding of the OWASP Top 10 for LLMs and how to mitigate risks related to prompt injection and AI-generated code vulnerabilities.
• Clearance:  Active TS/SCI clearance

Clearance Requirements:

• This position requires eligibility to obtain and maintain a security clearance up to TS/SCI

#LI-MS1

#Hybrid

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

The mission of Speechify is to make sure that reading is never a barrier to learning.

Over 50 million people use Speechify’s text-to-speech products to turn whatever they’re reading – PDFs, books, Google Docs, news articles, websites – into audio, so they can read faster, read more, and remember more. Speechify’s text-to-speech reading products include its iOS app, Android App, Mac App, Chrome Extension, and Web App. Google recently named Speechify the Chrome Extension of the Year and Apple named Speechify its 2025 Design Award winner for Inclusivity.  

Today, nearly 200 people around the globe work on Speechify in a 100% distributed setting – Speechify has no office. These include frontend and backend engineers, AI research scientists, and others from Amazon, Microsoft, and Google, leading PhD programs like Stanford, high growth startups like Stripe, Vercel, Bolt, and many founders of their own companies.

Overview

The responsibilities of our Platform team include building and maintaining all backend services, including, but not limited to, payments, analytics, subscriptions, new products, text to speech, and external APIs.

This is a key role and ideal for someone who thinks strategically, enjoys fast-paced environments, is passionate about making product decisions, and has experience building great user experiences that delight users.

We are a flat organization that allows anyone to become a leader by showing excellent technical skills and delivering results consistently and fast. Work ethic, solid communication skills, and obsession with winning are paramount. 

Our interview process involves several technical interviews and we aim to complete them within 1 week. 

What You’ll Do

• Design, develop, and maintain robust APIs including public TTS API, internal APIs like Payment, Subscription, Auth and Consumption Tracking, ensuring they meet business and scalability requirements
• Oversee the full backend API landscape, enhancing and optimizing for performance and maintainability
• Collaborate on B2B solutions, focusing on customization and integration needs for enterprise clients
• Work closely with cross-functional teams to align backend architecture with overall product strategy and user experience

An Ideal Candidate Should Have

• Proven experience in backend development: TS/Node (required)
• Direct experience with GCP and knowledge of AWS, Azure, or other cloud providers
• Efficiency in ideation and implementation, prioritizing tasks based on urgency and impact
• Preferred: Experience with Docker and containerized deployments
• Preferred: Proficiency in deploying high availability applications on Kubernetes

What We Offer

• A dynamic environment where your contributions shape the company and its products
• A team that values innovation, intuition, and drive
• Autonomy, fostering focus and creativity
• The opportunity to have a significant impact in a revolutionary industry
• Competitive compensation, a welcoming atmosphere, and a commitment to an exceptional asynchronous work culture
• The privilege of working on a product that changes lives, particularly for those with learning differences like dyslexia, ADD, and more
• An active role at the intersection of artificial intelligence and audio – a rapidly evolving tech domain

The United States Based Salary range for this role is: 140,000-200,000 USD/Year + Bonus + Stock depending on experience

Think you’re a good fit for this job? 

Tell us more about yourself and why you're interested in the role when you apply.
And don’t forget to include links to your portfolio and LinkedIn.

Not looking but know someone who would make a great fit? 

Refer them! 

Speechify is committed to a diverse and inclusive workplace. 

Speechify does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

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.