793 jobs found

Job Description Job Description Hi, We're AppFolio We're innovators, changemakers, and collaborators. We're more than just a software company - we're building the AI-native platform where the real estate industry comes to do business. We're transforming property management: how properties are leased, how residents find their homes, and how intelligence flows across an entire portfolio. Realm-X is AppFolio's AI-native platform powering this transformation. Within it, Realm-X Leasing Performer is an autonomous AI agent that handles the end-to-end leasing lifecycle - lead management, tour scheduling, follow-up, application processing, etc. - on behalf of property managers and leasing teams. It's one of AppFolio's most ambitious bets on autonomous AI, and it needs ML engineering worthy of that ambition. Who We Are Looking For We're hiring a Staff Machine Learning Engineer to own the ML strategy and execution that makes the Realm-X Leasing Performer production-grade, observable, and continuously improving. You'll sit at the intersection of applied ML, agent systems, and leasing domain expertise - working directly with Leasing Engineering, Voice & Agents, and Research ML to translate prototypes into systems our customers can depend on every day. This isn't a platform-only role. You'll be close enough to the product to shape how the Leasing Performer reasons, acts, and learns - and close enough to infrastructure to make sure it's reliable, cost-efficient, and safe at scale. Your Impact Own the ML Strategy for Leasing: Define and drive the machine learning roadmap across Leasing products - identifying where ML creates the most leverage, making the right model and architecture bets, and working closely with Product and Engineering leadership to align the team around a coherent technical vision that reflects real customer outcomes. Drive the Development & Architecture for Autonomous AI Agents: Be the ML lead for AppFolio's autonomous leasing agent - shaping how it communicates with prospective tenants and helps streamline leasing operations. You'll own the model quality, evaluation framework, and continuous improvement loop that makes the Performer better over time. Translate Research into Product: Partner with Voice & Agents and Research ML to evaluate new capabilities - fine-tuning approaches, retrieval strategies, agentic patterns - and make the call on what's ready to ship and what needs more hardening before it reaches customers. Drive Model Quality and Evaluation: Build the evaluation and experimentation infrastructure that lets the Leasing team ship ML changes with confidence - defining what "better" looks like for leasing-specific tasks and owning the metrics that reflect real customer outcomes. Set the ML Bar for Leasing Engineering: Establish the patterns, standards, and practices that the broader Leasing Engineering team follows when integrating ML - from prompt engineering and RAG to fine-tuning and model selection. Be the person the team comes to when the ML question is hard. Operate with Production Discipline: Ensure that ML systems powering the Leasing Performer meet the reliability bar that production SaaS demands - SLOs, observability, cost discipline, and a clear on-call posture. You don't have to build all of it, but you own the outcomes. Qualifications Systems thinker: You think in terms of platforms and long-term leverage, not just features. You understand how ML infrastructure decisions compound over time. Production builder: You've built and scaled ML infrastructure in production with meaningful business impact - and you treat it like any other production system. Domain curiosity: You take time to understand the business workflows your systems serve - in this case, leasing - and use that understanding to make better technical bets. Ambiguity: You operate effectively in high ambiguity, turning unclear infra problems into clear direction. Owner-operator: You take ownership with a founder mindset, act with urgency, and focus on outcomes. Collaboration: You are humble, collaborative, and low-ego - you elevate those around you and work fluidly across ML, product, and engineering. Reliability mindset: You treat ML infra like any other production system: SLOs, on-call, observability, postmortems. Sustainability: You value work-life balance as a foundation for sustained high performance. Must Have ML Development at scale: Has built and supported production ML systems at scale. Architectural Leadership: You have experience leading architectural discussions, defining system design, and guiding technical decision-making. Inference & Training: Has trained or fine-tuned language models end-to-end; comfortable with deep learning, evaluation, and inference. Training capability: Has trained or fine-tuned language models end-to-end; comfortable with deep learning, evaluation, and inference. RAG & agents: Hands-on experience with LangChain / LangGraph and modern RAG patterns over structured and unstructured data. AI safety & authorization: Hands-on experience operating AI guardrails, scoped tool permissions, and authorization layers for production AI systems - especially in agentic contexts. Nice to Have Experience building ML systems for conversational AI, leasing, or CRM-adjacent workflows. GPU performance tuning (vLLM, TensorRT, Triton, or similar). Experience with ontology-driven systems or knowledge graphs supporting AI applications. Familiarity with real estate, property management, or leasing workflows. Contributions to open-source ML infrastructure or LLM tooling. Location Find out more about our locations by visiting our site. All late-stage candidates complete an in-person meeting with an AppFolian as part of our hiring process. Compensation & Benefits The compensation that we reasonably expect to pay for this role is: $200,000 - $275,000 base pay. The actual compensation for this role will be determined by a variety of factors, including but not limited to the candidate's skills, education, experience, and internal equity. Please note that compensation is just one aspect of a comprehensive Total Rewards package. The compensation range listed here does not include additional benefits or any discretionary bonuses you may be eligible for based on your role and/or employment type. Regular full-time employees are eligible for benefits - see here.

Job Description Job Description Hi, We're AppFolio We're innovators, changemakers, and collaborators. We're more than just a software company - we're building the AI-native platform where the real estate industry comes to do business. We're transforming property management: how properties are leased, how residents find their homes, and how intelligence flows across an entire portfolio. Realm-X is AppFolio's AI-native platform powering this transformation. Within it, Realm-X Leasing Performer is an autonomous AI agent that handles the end-to-end leasing lifecycle - lead management, tour scheduling, follow-up, application processing, etc. - on behalf of property managers and leasing teams. It's one of AppFolio's most ambitious bets on autonomous AI, and it needs ML engineering worthy of that ambition. Who We Are Looking For We're hiring a Staff Machine Learning Engineer to own the ML strategy and execution that makes the Realm-X Leasing Performer production-grade, observable, and continuously improving. You'll sit at the intersection of applied ML, agent systems, and leasing domain expertise - working directly with Leasing Engineering, Voice & Agents, and Research ML to translate prototypes into systems our customers can depend on every day. This isn't a platform-only role. You'll be close enough to the product to shape how the Leasing Performer reasons, acts, and learns - and close enough to infrastructure to make sure it's reliable, cost-efficient, and safe at scale. Your Impact Own the ML Strategy for Leasing: Define and drive the machine learning roadmap across Leasing products - identifying where ML creates the most leverage, making the right model and architecture bets, and working closely with Product and Engineering leadership to align the team around a coherent technical vision that reflects real customer outcomes. Drive the Development & Architecture for Autonomous AI Agents: Be the ML lead for AppFolio's autonomous leasing agent - shaping how it communicates with prospective tenants and helps streamline leasing operations. You'll own the model quality, evaluation framework, and continuous improvement loop that makes the Performer better over time. Translate Research into Product: Partner with Voice & Agents and Research ML to evaluate new capabilities - fine-tuning approaches, retrieval strategies, agentic patterns - and make the call on what's ready to ship and what needs more hardening before it reaches customers. Drive Model Quality and Evaluation: Build the evaluation and experimentation infrastructure that lets the Leasing team ship ML changes with confidence - defining what "better" looks like for leasing-specific tasks and owning the metrics that reflect real customer outcomes. Set the ML Bar for Leasing Engineering: Establish the patterns, standards, and practices that the broader Leasing Engineering team follows when integrating ML - from prompt engineering and RAG to fine-tuning and model selection. Be the person the team comes to when the ML question is hard. Operate with Production Discipline: Ensure that ML systems powering the Leasing Performer meet the reliability bar that production SaaS demands - SLOs, observability, cost discipline, and a clear on-call posture. You don't have to build all of it, but you own the outcomes. Qualifications Systems thinker: You think in terms of platforms and long-term leverage, not just features. You understand how ML infrastructure decisions compound over time. Production builder: You've built and scaled ML infrastructure in production with meaningful business impact - and you treat it like any other production system. Domain curiosity: You take time to understand the business workflows your systems serve - in this case, leasing - and use that understanding to make better technical bets. Ambiguity: You operate effectively in high ambiguity, turning unclear infra problems into clear direction. Owner-operator: You take ownership with a founder mindset, act with urgency, and focus on outcomes. Collaboration: You are humble, collaborative, and low-ego - you elevate those around you and work fluidly across ML, product, and engineering. Reliability mindset: You treat ML infra like any other production system: SLOs, on-call, observability, postmortems. Sustainability: You value work-life balance as a foundation for sustained high performance. Must Have ML Development at scale: Has built and supported production ML systems at scale. Architectural Leadership: You have experience leading architectural discussions, defining system design, and guiding technical decision-making. Inference & Training: Has trained or fine-tuned language models end-to-end; comfortable with deep learning, evaluation, and inference. Training capability: Has trained or fine-tuned language models end-to-end; comfortable with deep learning, evaluation, and inference. RAG & agents: Hands-on experience with LangChain / LangGraph and modern RAG patterns over structured and unstructured data. AI safety & authorization: Hands-on experience operating AI guardrails, scoped tool permissions, and authorization layers for production AI systems - especially in agentic contexts. Nice to Have Experience building ML systems for conversational AI, leasing, or CRM-adjacent workflows. GPU performance tuning (vLLM, TensorRT, Triton, or similar). Experience with ontology-driven systems or knowledge graphs supporting AI applications. Familiarity with real estate, property management, or leasing workflows. Contributions to open-source ML infrastructure or LLM tooling. Location Find out more about our locations by visiting our site. All late-stage candidates complete an in-person meeting with an AppFolian as part of our hiring process. Compensation & Benefits The compensation that we reasonably expect to pay for this role is: $200,000 - $275,000 base pay. The actual compensation for this role will be determined by a variety of factors, including but not limited to the candidate's skills, education, experience, and internal equity. Please note that compensation is just one aspect of a comprehensive Total Rewards package. The compensation range listed here does not include additional benefits or any discretionary bonuses you may be eligible for based on your role and/or employment type. Regular full-time employees are eligible for benefits - see here.

Job Description Job Description Hi, We're AppFolio We're innovators, changemakers, and collaborators. We're more than just a software company - we're building the AI-native platform where the real estate industry comes to do business. We're transforming property management: how properties are leased, how residents find their homes, and how intelligence flows across an entire portfolio. Realm-X is AppFolio's AI-native platform powering this transformation. Within it, Realm-X Leasing Performer is an autonomous AI agent that handles the end-to-end leasing lifecycle - lead management, tour scheduling, follow-up, application processing, etc. - on behalf of property managers and leasing teams. It's one of AppFolio's most ambitious bets on autonomous AI, and it needs ML engineering worthy of that ambition. Who We Are Looking For We're hiring a Staff Machine Learning Engineer to own the ML strategy and execution that makes the Realm-X Leasing Performer production-grade, observable, and continuously improving. You'll sit at the intersection of applied ML, agent systems, and leasing domain expertise - working directly with Leasing Engineering, Voice & Agents, and Research ML to translate prototypes into systems our customers can depend on every day. This isn't a platform-only role. You'll be close enough to the product to shape how the Leasing Performer reasons, acts, and learns - and close enough to infrastructure to make sure it's reliable, cost-efficient, and safe at scale. Your Impact Own the ML Strategy for Leasing: Define and drive the machine learning roadmap across Leasing products - identifying where ML creates the most leverage, making the right model and architecture bets, and working closely with Product and Engineering leadership to align the team around a coherent technical vision that reflects real customer outcomes. Drive the Development & Architecture for Autonomous AI Agents: Be the ML lead for AppFolio's autonomous leasing agent - shaping how it communicates with prospective tenants and helps streamline leasing operations. You'll own the model quality, evaluation framework, and continuous improvement loop that makes the Performer better over time. Translate Research into Product: Partner with Voice & Agents and Research ML to evaluate new capabilities - fine-tuning approaches, retrieval strategies, agentic patterns - and make the call on what's ready to ship and what needs more hardening before it reaches customers. Drive Model Quality and Evaluation: Build the evaluation and experimentation infrastructure that lets the Leasing team ship ML changes with confidence - defining what "better" looks like for leasing-specific tasks and owning the metrics that reflect real customer outcomes. Set the ML Bar for Leasing Engineering: Establish the patterns, standards, and practices that the broader Leasing Engineering team follows when integrating ML - from prompt engineering and RAG to fine-tuning and model selection. Be the person the team comes to when the ML question is hard. Operate with Production Discipline: Ensure that ML systems powering the Leasing Performer meet the reliability bar that production SaaS demands - SLOs, observability, cost discipline, and a clear on-call posture. You don't have to build all of it, but you own the outcomes. Qualifications Systems thinker: You think in terms of platforms and long-term leverage, not just features. You understand how ML infrastructure decisions compound over time. Production builder: You've built and scaled ML infrastructure in production with meaningful business impact - and you treat it like any other production system. Domain curiosity: You take time to understand the business workflows your systems serve - in this case, leasing - and use that understanding to make better technical bets. Ambiguity: You operate effectively in high ambiguity, turning unclear infra problems into clear direction. Owner-operator: You take ownership with a founder mindset, act with urgency, and focus on outcomes. Collaboration: You are humble, collaborative, and low-ego - you elevate those around you and work fluidly across ML, product, and engineering. Reliability mindset: You treat ML infra like any other production system: SLOs, on-call, observability, postmortems. Sustainability: You value work-life balance as a foundation for sustained high performance. Must Have ML Development at scale: Has built and supported production ML systems at scale. Architectural Leadership: You have experience leading architectural discussions, defining system design, and guiding technical decision-making. Inference & Training: Has trained or fine-tuned language models end-to-end; comfortable with deep learning, evaluation, and inference. Training capability: Has trained or fine-tuned language models end-to-end; comfortable with deep learning, evaluation, and inference. RAG & agents: Hands-on experience with LangChain / LangGraph and modern RAG patterns over structured and unstructured data. AI safety & authorization: Hands-on experience operating AI guardrails, scoped tool permissions, and authorization layers for production AI systems - especially in agentic contexts. Nice to Have Experience building ML systems for conversational AI, leasing, or CRM-adjacent workflows. GPU performance tuning (vLLM, TensorRT, Triton, or similar). Experience with ontology-driven systems or knowledge graphs supporting AI applications. Familiarity with real estate, property management, or leasing workflows. Contributions to open-source ML infrastructure or LLM tooling. Location Find out more about our locations by visiting our site. All late-stage candidates complete an in-person meeting with an AppFolian as part of our hiring process. Compensation & Benefits The compensation that we reasonably expect to pay for this role is: $200,000 - $275,000 base pay. The actual compensation for this role will be determined by a variety of factors, including but not limited to the candidate's skills, education, experience, and internal equity. Please note that compensation is just one aspect of a comprehensive Total Rewards package. The compensation range listed here does not include additional benefits or any discretionary bonuses you may be eligible for based on your role and/or employment type. Regular full-time employees are eligible for benefits - see here.

Job Description Job Description Position Summary: The Robotic Welding Programmer is responsible for programming, configuring, and optimizing robotic welding systems to produce high-quality welded products safely and efficiently. This role troubleshoots robotic welding systems and works closely with engineering, quality, and production teams to support manufacturing operations. Primary Responsibilities: Program and optimize robotic welding systems for new and existing products. Create, modify, and troubleshoot robot programs using teach pendants and offline programming software where applicable. Develop weld paths, torch angles, travel speeds, and welding parameters to ensure quality and productivity. Set up robotic welding cells for new product launches and engineering changes. Troubleshoot robot programming, welding quality, and equipment issues. Optimize cycle times while maintaining safety and product quality. Perform robot backups, software updates, and program documentation. Collaborate with engineering to design fixtures and improve manufacturability. Support preventive maintenance and equipment calibration activities. Analyze weld quality and implement corrective actions for defects. Train operators and technicians on proper robot operation and basic troubleshooting. Read and interpret engineering drawings, GD&T, weld symbols, and specifications. Support continuous improvement initiatives using Lean manufacturing principles. Ensure compliance with safety standards, company policies, and customer requirements. Perform other duties as required or assigned. Qualifications: High school diploma or GED required; associate degree or technical certification in robotics, welding, manufacturing, or a related field preferred. 3-5 years of robotic welding programming experience in a manufacturing environment. Experience with MIG (GMAW) and/or TIG (GTAW) welding processes. Experience programming one or more robotic platforms. Knowledge of robotic welding power sources. Strong understanding of robotic programming principles and motion optimization. Knowledge of welding metallurgy and welding procedures. Ability to troubleshoot robot hardware, software, sensors, and welding equipment. Ability to interpret blueprints, weld symbols, and geometric dimensioning and tolerancing (GD&T). Experience with offline programming software is preferred. Minimum Physical Requirements and Accountability: Work often involves extended periods of standing, walking, and performing repetitive or physically demanding tasks. Effective verbal communication and hearing are essential for maintaining safety, receiving instructions, and coordinating with team members in person, over radios, or through alarms. Both fine motor skills (e.g., handling small components, precision work) and gross motor skills (e.g., operating tools and heavy equipment) are critical. Visual acuity is required for reading blueprints, measuring materials, performing precision work, and maintaining situational awareness; near, far, and peripheral vision may all be needed. Must be able to work in a variety of environments, including indoor and outdoor settings, as well as dusty, loud, hot, cold, or potentially hazardous areas. Tasks may involve bending, stooping, reaching overhead or below shoulder height, crouching, kneeling, climbing ladders or ramps, and maintaining balance on uneven surfaces. Must be able to work at heights, in confined spaces, or in other challenging physical locations as required by the task. Must be able to lift, carry, push, or pull up to 50 lbs independently. Must comply with all company policies and procedures. Consistent, punctual attendance during core business hours is essential. Reliable transportation is required for commuting and occasional travel between local corporate offices and job sites during business hours. All employees are accountable for safety and health and are empowered to stop work if an unsafe condition is present. Employees should immediately notify their supervisor so that the hazard may be corrected. What Sets RK Industries Apart Safety: Our unmatched culture of safety is our foremost core value, guiding everything we do each day: Health, Safety, & Environmental Awards: Whether in Construction, Manufacturing, Fabrication, or Service, RK Industries is highly recognized and accredited throughout the industry: Accreditations & Recognition Benefits: RK Industries offers competitive benefits to support your growth and well-being: Benefits & Rewards Philanthropy: RK Industries not only builds our community through our projects, but also invests in it by supporting local services for over a decade through the RK Foundation: RK Foundation Development: Through RK University, we provide hands-on training and development opportunities that empower employees to advance their careers and grow within the company, to include leadership and technical learning opportunities, we well as our accredited apprentice program: RK University & RK Apprenticeship Program Applications are accepted on an ongoing basis.

Job Description Job Description Position Summary: The Robotic Welding Programmer is responsible for programming, configuring, and optimizing robotic welding systems to produce high-quality welded products safely and efficiently. This role troubleshoots robotic welding systems and works closely with engineering, quality, and production teams to support manufacturing operations. Primary Responsibilities: Program and optimize robotic welding systems for new and existing products. Create, modify, and troubleshoot robot programs using teach pendants and offline programming software where applicable. Develop weld paths, torch angles, travel speeds, and welding parameters to ensure quality and productivity. Set up robotic welding cells for new product launches and engineering changes. Troubleshoot robot programming, welding quality, and equipment issues. Optimize cycle times while maintaining safety and product quality. Perform robot backups, software updates, and program documentation. Collaborate with engineering to design fixtures and improve manufacturability. Support preventive maintenance and equipment calibration activities. Analyze weld quality and implement corrective actions for defects. Train operators and technicians on proper robot operation and basic troubleshooting. Read and interpret engineering drawings, GD&T, weld symbols, and specifications. Support continuous improvement initiatives using Lean manufacturing principles. Ensure compliance with safety standards, company policies, and customer requirements. Perform other duties as required or assigned. Qualifications: High school diploma or GED required; associate degree or technical certification in robotics, welding, manufacturing, or a related field preferred. 3-5 years of robotic welding programming experience in a manufacturing environment. Experience with MIG (GMAW) and/or TIG (GTAW) welding processes. Experience programming one or more robotic platforms. Knowledge of robotic welding power sources. Strong understanding of robotic programming principles and motion optimization. Knowledge of welding metallurgy and welding procedures. Ability to troubleshoot robot hardware, software, sensors, and welding equipment. Ability to interpret blueprints, weld symbols, and geometric dimensioning and tolerancing (GD&T). Experience with offline programming software is preferred. Minimum Physical Requirements and Accountability: Work often involves extended periods of standing, walking, and performing repetitive or physically demanding tasks. Effective verbal communication and hearing are essential for maintaining safety, receiving instructions, and coordinating with team members in person, over radios, or through alarms. Both fine motor skills (e.g., handling small components, precision work) and gross motor skills (e.g., operating tools and heavy equipment) are critical. Visual acuity is required for reading blueprints, measuring materials, performing precision work, and maintaining situational awareness; near, far, and peripheral vision may all be needed. Must be able to work in a variety of environments, including indoor and outdoor settings, as well as dusty, loud, hot, cold, or potentially hazardous areas. Tasks may involve bending, stooping, reaching overhead or below shoulder height, crouching, kneeling, climbing ladders or ramps, and maintaining balance on uneven surfaces. Must be able to work at heights, in confined spaces, or in other challenging physical locations as required by the task. Must be able to lift, carry, push, or pull up to 50 lbs independently. Must comply with all company policies and procedures. Consistent, punctual attendance during core business hours is essential. Reliable transportation is required for commuting and occasional travel between local corporate offices and job sites during business hours. All employees are accountable for safety and health and are empowered to stop work if an unsafe condition is present. Employees should immediately notify their supervisor so that the hazard may be corrected. What Sets RK Industries Apart Safety: Our unmatched culture of safety is our foremost core value, guiding everything we do each day: Health, Safety, & Environmental Awards: Whether in Construction, Manufacturing, Fabrication, or Service, RK Industries is highly recognized and accredited throughout the industry: Accreditations & Recognition Benefits: RK Industries offers competitive benefits to support your growth and well-being: Benefits & Rewards Philanthropy: RK Industries not only builds our community through our projects, but also invests in it by supporting local services for over a decade through the RK Foundation: RK Foundation Development: Through RK University, we provide hands-on training and development opportunities that empower employees to advance their careers and grow within the company, to include leadership and technical learning opportunities, we well as our accredited apprentice program: RK University & RK Apprenticeship Program Applications are accepted on an ongoing basis.

Job Description Job Description Description FII USA, Inc ., a Foxconn Technology Group Company, is seeking a Failure Analysis Engineer to perform engineering investigations of significant customer field and line escalations related to hardware issues and collaborate with numerous internal engineering disciplines to resolve hardware issues. Once a part of the team, you will be responsible for a wide variety of tasks within the Supporting Quality Department in an office environment and have the opportunity to display critical thinking skills to expand your career in Smart Manufacturing. The Failure Analysis Engineer will monitor test failure trends in NPI, provide corrective actions to improve production test yields, and assist this Supporting Quality Department as needed. Responsibilities Interface with customers and internal cross-functional teams to root cause hardware issues to the component level Perform engineering investigations of significant customer field and line escalations related to hardware issues Monitor test failure trends in NPI and provide corrective actions to improve production test yields Design and develop debug tools to improve debug process and efficiency Provide training to technicians and debug team on new and existing debug procedures and product troubleshooting Support internal communications of techniques and processes for WW RMA & Service Centers Drive "best practices" across WW Operational, RMA & Service Sites Program manage CSP/Enterprise account Reliability requirements Facilitate Reliability strategy discussions Other duties as assigned Qualifications Bachelor's or Master's degree in electrical or computer engineering required Minimum of 4 years' experience designing and debugging Industry Standard Computing platforms required Experience in hardware/firmware/software development and test methodologies preferred Knowledge of key server technologies including Intel, AMD, ARM multi-core microprocessors, DDR 4/5 and NAND memory, and PCA design preferred Reasons you should work for us: Comprehensive benefits package including medical, dental, and vision insurance coverage. Basic life insurance and short-term disability coverage provided by employer. Supplemental life insurance and long-term disability coverage options available. 401K with employer contribution. Personal, Vacation, and Holiday paid time off for all full-time employees. Onsite Aurora Health & Wellness Center available for all employees. Employees are continuously encouraged to learn and grow their careers in smart manufacturing.

Job Description Job Description Note: This role is full - time 40 hours per week and will require support (5pm -10pm) on Tuesdays and Wednesday Target Salary $118K Location: Suitland, MD Candidate must be able to obtain Public Trust (federal government background investigation, with eligibility requirement - US Citizen) Data Center Hardware & Cabling Engineer ActioNet has an opening for an experienced, hands-on Data Center Hardware & Cabling Enginee r to join our infrastructure team. This role ensures that our servers, networking gear, and storage systems are installed, organized, and tracked. The candidate will work with team members who possess diverse backgrounds (systems engineering, system administration) and will be part of a Government Contractor Team working at Census Data Center in Bowie, MD. If you take pride in a perfectly dressed server rack and find satisfaction in a 100% accurate asset database, you'll fit right in. Key Responsibilities 1. Hardware Deployment & Maintenance Rack & Stack: Physically install, bolt, and secure servers, switches, and PDUs into high-density racks. Component Replacement: Perform "smart hands" tasks including swapping failed DIMMs, CPUs, hard drives, and power supplies. Troubleshooting: Diagnose physical layer issues and work with remote engineering teams to restore service. Must be available weekends and evenings 25% of the year. 2. Cable Management Installation: Install and maintain structured cabling in a datacenter environment including Cat 5, Cat 6 and Fiber optic network cabling, including termination of Fiber and Copper. Must be able to work evening shifts on Tuesday and Wednesday. Organization: Implement cable dressing standards to ensure airflow and maintainability. Establish network connection through accurate documentation and communication with Telecommunication offices. Labeling: Maintain a rigorous labeling convention for every cable at both termination points to ensure "traceability" without manual hunting. 3. Asset & Inventory Management Lifecycle Tracking: Utilize DCIM (Data Center Infrastructure Management) tools to track equipment from "dock to grave." Auditing: Conduct regular physical audits to ensure the digital inventory matches the physical reality of the floor. Perform general datacenter walkthroughs. RMA Management: Handle the shipping and receiving of defective parts, ensuring all serial numbers are logged and warranties are leveraged. Required Skills & Qualifications Physical Stamina: Ability to lift up to 50 lbs and work on ladders or in confined spaces for extended periods. Technical Knowledge: Deep understanding of TIA/EIA cabling standards, fiber polarity, and connector types (LC, SC, MPO). Tool Proficiency: Expert use of cable testers (Fluke), label makers, and basic power tools. Organization: Must present an eye for detail regarding cable routing and database accuracy for Datacenter and Computer Room Assets. Must be able to maintain electronic records on datacenter infrastructure. Education/Experience: 2+ years of experience in a production data center environment or a degree in a relevant technical field. Certifications Required - Certified Network Cable Installer (CNCI ) or BISCI Technician Certification or higher Nice to Have - CompTIA Server+ or Network+ ActioNet is a CMMI-DEV Level 4, CMMI-SVC Level 4, ISO 20000, ISO 27001, ISO 9001, HDI-certified, woman-owned IT Solutions Provider with strong qualifications and expertise in Agile Software Engineering, Cloud Solutions, Cyber Security and IT Managed Services. With 26+ years of stellar past performance, ActioNet is the premier Trusted Innogrator! Core Capabilities: Advanced and Managed IT Services Agile Software Development DevSecOps Cybersecurity Health IT C4ISR & SIGINT Data Center Engineering & Operations Engineering & Installation Why ActioNet? At ActioNet, our Passion for Quality is at the heart of everything we do: Commitment to Employees: We are committed to making ActioNet a great place to work and continue to invest in our ActioNeters. Commitment to Customers: We are committed to our customers by driving and sustaining Service Delivery Excellence. Commitment to Community: We are committed to giving back to our community, helping others, and making the world a better place for our next generation. ActioNet is proud to be named a Top Workplace for the twelfth year in a row (2014 - 2025). We have a 98% customer retention rate. We are passionate about the inspirational missions of our customers, and we entrust our employees and teams to deliver exceptional performance to enable the safety, security, health, and well-being of our nation. What's in It For You? As an ActioNeter, you get to be part of an exceptional team and a corporate culture that nurtures mutual success for our customers, employees, and communities. We give you the tools to be successful; all you need to do is bring your best ideas, your energy, and a desire to develop your skills, experience, and career. Are you ready to make a difference? ActioNet is an equal-opportunity employer and values inclusion at our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. Full-Time Employees are eligible to participate in our ActioNet's Benefits Program: Medical Insurance Vision Insurance Dental Insurance Life and AD&D Insurance 401(k) Savings Plan Education and Professional Training Flexible Spending Accounts (FSA) Employee Referral and Merit Recognition Programs Employee Assistance and Identity Theft Protection Paid Holidays: 11 per year Paid Time Off (PTO) Disability Insurance ActioNet is an equal opportunity employer and value inclusion at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. Direct Applicants, only. No Agencies, No third-party recruiters, please

Job Description Job Description Hi, We're AppFolio We're innovators, changemakers, and collaborators. We're more than just a software company - we're building the AI-native platform where the real estate industry comes to do business. We're transforming property management: how properties are leased, how residents find their homes, and how intelligence flows across an entire portfolio. Realm-X is AppFolio's AI-native platform powering this transformation. Within it, Realm-X Leasing Performer is an autonomous AI agent that handles the end-to-end leasing lifecycle - lead management, tour scheduling, follow-up, application processing, etc. - on behalf of property managers and leasing teams. It's one of AppFolio's most ambitious bets on autonomous AI, and it needs ML engineering worthy of that ambition. Who We Are Looking For We're hiring a Staff Machine Learning Engineer to own the ML strategy and execution that makes the Realm-X Leasing Performer production-grade, observable, and continuously improving. You'll sit at the intersection of applied ML, agent systems, and leasing domain expertise - working directly with Leasing Engineering, Voice & Agents, and Research ML to translate prototypes into systems our customers can depend on every day. This isn't a platform-only role. You'll be close enough to the product to shape how the Leasing Performer reasons, acts, and learns - and close enough to infrastructure to make sure it's reliable, cost-efficient, and safe at scale. Your Impact Own the ML Strategy for Leasing: Define and drive the machine learning roadmap across Leasing products - identifying where ML creates the most leverage, making the right model and architecture bets, and working closely with Product and Engineering leadership to align the team around a coherent technical vision that reflects real customer outcomes. Drive the Development & Architecture for Autonomous AI Agents: Be the ML lead for AppFolio's autonomous leasing agent - shaping how it communicates with prospective tenants and helps streamline leasing operations. You'll own the model quality, evaluation framework, and continuous improvement loop that makes the Performer better over time. Translate Research into Product: Partner with Voice & Agents and Research ML to evaluate new capabilities - fine-tuning approaches, retrieval strategies, agentic patterns - and make the call on what's ready to ship and what needs more hardening before it reaches customers. Drive Model Quality and Evaluation: Build the evaluation and experimentation infrastructure that lets the Leasing team ship ML changes with confidence - defining what "better" looks like for leasing-specific tasks and owning the metrics that reflect real customer outcomes. Set the ML Bar for Leasing Engineering: Establish the patterns, standards, and practices that the broader Leasing Engineering team follows when integrating ML - from prompt engineering and RAG to fine-tuning and model selection. Be the person the team comes to when the ML question is hard. Operate with Production Discipline: Ensure that ML systems powering the Leasing Performer meet the reliability bar that production SaaS demands - SLOs, observability, cost discipline, and a clear on-call posture. You don't have to build all of it, but you own the outcomes. Qualifications Systems thinker: You think in terms of platforms and long-term leverage, not just features. You understand how ML infrastructure decisions compound over time. Production builder: You've built and scaled ML infrastructure in production with meaningful business impact - and you treat it like any other production system. Domain curiosity: You take time to understand the business workflows your systems serve - in this case, leasing - and use that understanding to make better technical bets. Ambiguity: You operate effectively in high ambiguity, turning unclear infra problems into clear direction. Owner-operator: You take ownership with a founder mindset, act with urgency, and focus on outcomes. Collaboration: You are humble, collaborative, and low-ego - you elevate those around you and work fluidly across ML, product, and engineering. Reliability mindset: You treat ML infra like any other production system: SLOs, on-call, observability, postmortems. Sustainability: You value work-life balance as a foundation for sustained high performance. Must Have ML Development at scale: Has built and supported production ML systems at scale. Architectural Leadership: You have experience leading architectural discussions, defining system design, and guiding technical decision-making. Inference & Training: Has trained or fine-tuned language models end-to-end; comfortable with deep learning, evaluation, and inference. Training capability: Has trained or fine-tuned language models end-to-end; comfortable with deep learning, evaluation, and inference. RAG & agents: Hands-on experience with LangChain / LangGraph and modern RAG patterns over structured and unstructured data. AI safety & authorization: Hands-on experience operating AI guardrails, scoped tool permissions, and authorization layers for production AI systems - especially in agentic contexts. Nice to Have Experience building ML systems for conversational AI, leasing, or CRM-adjacent workflows. GPU performance tuning (vLLM, TensorRT, Triton, or similar). Experience with ontology-driven systems or knowledge graphs supporting AI applications. Familiarity with real estate, property management, or leasing workflows. Contributions to open-source ML infrastructure or LLM tooling. Location Find out more about our locations by visiting our site. All late-stage candidates complete an in-person meeting with an AppFolian as part of our hiring process. Compensation & Benefits The compensation that we reasonably expect to pay for this role is: $200,000 - $275,000 base pay. The actual compensation for this role will be determined by a variety of factors, including but not limited to the candidate's skills, education, experience, and internal equity. Please note that compensation is just one aspect of a comprehensive Total Rewards package. The compensation range listed here does not include additional benefits or any discretionary bonuses you may be eligible for based on your role and/or employment type. Regular full-time employees are eligible for benefits - see here.

Job Description Job Description Hi, We're AppFolio We're innovators, changemakers, and collaborators. We're more than just a software company - we're building the AI-native platform where the real estate industry comes to do business. We're transforming property management: how properties are leased, how residents find their homes, and how intelligence flows across an entire portfolio. Realm-X is AppFolio's AI-native platform powering this transformation. Within it, Realm-X Leasing Performer is an autonomous AI agent that handles the end-to-end leasing lifecycle - lead management, tour scheduling, follow-up, application processing, etc. - on behalf of property managers and leasing teams. It's one of AppFolio's most ambitious bets on autonomous AI, and it needs ML engineering worthy of that ambition. Who We Are Looking For We're hiring a Staff Machine Learning Engineer to own the ML strategy and execution that makes the Realm-X Leasing Performer production-grade, observable, and continuously improving. You'll sit at the intersection of applied ML, agent systems, and leasing domain expertise - working directly with Leasing Engineering, Voice & Agents, and Research ML to translate prototypes into systems our customers can depend on every day. This isn't a platform-only role. You'll be close enough to the product to shape how the Leasing Performer reasons, acts, and learns - and close enough to infrastructure to make sure it's reliable, cost-efficient, and safe at scale. Your Impact Own the ML Strategy for Leasing: Define and drive the machine learning roadmap across Leasing products - identifying where ML creates the most leverage, making the right model and architecture bets, and working closely with Product and Engineering leadership to align the team around a coherent technical vision that reflects real customer outcomes. Drive the Development & Architecture for Autonomous AI Agents: Be the ML lead for AppFolio's autonomous leasing agent - shaping how it communicates with prospective tenants and helps streamline leasing operations. You'll own the model quality, evaluation framework, and continuous improvement loop that makes the Performer better over time. Translate Research into Product: Partner with Voice & Agents and Research ML to evaluate new capabilities - fine-tuning approaches, retrieval strategies, agentic patterns - and make the call on what's ready to ship and what needs more hardening before it reaches customers. Drive Model Quality and Evaluation: Build the evaluation and experimentation infrastructure that lets the Leasing team ship ML changes with confidence - defining what "better" looks like for leasing-specific tasks and owning the metrics that reflect real customer outcomes. Set the ML Bar for Leasing Engineering: Establish the patterns, standards, and practices that the broader Leasing Engineering team follows when integrating ML - from prompt engineering and RAG to fine-tuning and model selection. Be the person the team comes to when the ML question is hard. Operate with Production Discipline: Ensure that ML systems powering the Leasing Performer meet the reliability bar that production SaaS demands - SLOs, observability, cost discipline, and a clear on-call posture. You don't have to build all of it, but you own the outcomes. Qualifications Systems thinker: You think in terms of platforms and long-term leverage, not just features. You understand how ML infrastructure decisions compound over time. Production builder: You've built and scaled ML infrastructure in production with meaningful business impact - and you treat it like any other production system. Domain curiosity: You take time to understand the business workflows your systems serve - in this case, leasing - and use that understanding to make better technical bets. Ambiguity: You operate effectively in high ambiguity, turning unclear infra problems into clear direction. Owner-operator: You take ownership with a founder mindset, act with urgency, and focus on outcomes. Collaboration: You are humble, collaborative, and low-ego - you elevate those around you and work fluidly across ML, product, and engineering. Reliability mindset: You treat ML infra like any other production system: SLOs, on-call, observability, postmortems. Sustainability: You value work-life balance as a foundation for sustained high performance. Must Have ML Development at scale: Has built and supported production ML systems at scale. Architectural Leadership: You have experience leading architectural discussions, defining system design, and guiding technical decision-making. Inference & Training: Has trained or fine-tuned language models end-to-end; comfortable with deep learning, evaluation, and inference. Training capability: Has trained or fine-tuned language models end-to-end; comfortable with deep learning, evaluation, and inference. RAG & agents: Hands-on experience with LangChain / LangGraph and modern RAG patterns over structured and unstructured data. AI safety & authorization: Hands-on experience operating AI guardrails, scoped tool permissions, and authorization layers for production AI systems - especially in agentic contexts. Nice to Have Experience building ML systems for conversational AI, leasing, or CRM-adjacent workflows. GPU performance tuning (vLLM, TensorRT, Triton, or similar). Experience with ontology-driven systems or knowledge graphs supporting AI applications. Familiarity with real estate, property management, or leasing workflows. Contributions to open-source ML infrastructure or LLM tooling. Location Find out more about our locations by visiting our site. All late-stage candidates complete an in-person meeting with an AppFolian as part of our hiring process. Compensation & Benefits The compensation that we reasonably expect to pay for this role is: $200,000 - $275,000 base pay. The actual compensation for this role will be determined by a variety of factors, including but not limited to the candidate's skills, education, experience, and internal equity. Please note that compensation is just one aspect of a comprehensive Total Rewards package. The compensation range listed here does not include additional benefits or any discretionary bonuses you may be eligible for based on your role and/or employment type. Regular full-time employees are eligible for benefits - see here.

Job Description Job Description Hi, We're AppFolio We're innovators, changemakers, and collaborators. We're more than just a software company - we're building the AI-native platform where the real estate industry comes to do business. We're transforming property management: how properties are leased, how residents find their homes, and how intelligence flows across an entire portfolio. Realm-X is AppFolio's AI-native platform powering this transformation. Within it, Realm-X Leasing Performer is an autonomous AI agent that handles the end-to-end leasing lifecycle - lead management, tour scheduling, follow-up, application processing, etc. - on behalf of property managers and leasing teams. It's one of AppFolio's most ambitious bets on autonomous AI, and it needs ML engineering worthy of that ambition. Who We Are Looking For We're hiring a Staff Machine Learning Engineer to own the ML strategy and execution that makes the Realm-X Leasing Performer production-grade, observable, and continuously improving. You'll sit at the intersection of applied ML, agent systems, and leasing domain expertise - working directly with Leasing Engineering, Voice & Agents, and Research ML to translate prototypes into systems our customers can depend on every day. This isn't a platform-only role. You'll be close enough to the product to shape how the Leasing Performer reasons, acts, and learns - and close enough to infrastructure to make sure it's reliable, cost-efficient, and safe at scale. Your Impact Own the ML Strategy for Leasing: Define and drive the machine learning roadmap across Leasing products - identifying where ML creates the most leverage, making the right model and architecture bets, and working closely with Product and Engineering leadership to align the team around a coherent technical vision that reflects real customer outcomes. Drive the Development & Architecture for Autonomous AI Agents: Be the ML lead for AppFolio's autonomous leasing agent - shaping how it communicates with prospective tenants and helps streamline leasing operations. You'll own the model quality, evaluation framework, and continuous improvement loop that makes the Performer better over time. Translate Research into Product: Partner with Voice & Agents and Research ML to evaluate new capabilities - fine-tuning approaches, retrieval strategies, agentic patterns - and make the call on what's ready to ship and what needs more hardening before it reaches customers. Drive Model Quality and Evaluation: Build the evaluation and experimentation infrastructure that lets the Leasing team ship ML changes with confidence - defining what "better" looks like for leasing-specific tasks and owning the metrics that reflect real customer outcomes. Set the ML Bar for Leasing Engineering: Establish the patterns, standards, and practices that the broader Leasing Engineering team follows when integrating ML - from prompt engineering and RAG to fine-tuning and model selection. Be the person the team comes to when the ML question is hard. Operate with Production Discipline: Ensure that ML systems powering the Leasing Performer meet the reliability bar that production SaaS demands - SLOs, observability, cost discipline, and a clear on-call posture. You don't have to build all of it, but you own the outcomes. Qualifications Systems thinker: You think in terms of platforms and long-term leverage, not just features. You understand how ML infrastructure decisions compound over time. Production builder: You've built and scaled ML infrastructure in production with meaningful business impact - and you treat it like any other production system. Domain curiosity: You take time to understand the business workflows your systems serve - in this case, leasing - and use that understanding to make better technical bets. Ambiguity: You operate effectively in high ambiguity, turning unclear infra problems into clear direction. Owner-operator: You take ownership with a founder mindset, act with urgency, and focus on outcomes. Collaboration: You are humble, collaborative, and low-ego - you elevate those around you and work fluidly across ML, product, and engineering. Reliability mindset: You treat ML infra like any other production system: SLOs, on-call, observability, postmortems. Sustainability: You value work-life balance as a foundation for sustained high performance. Must Have ML Development at scale: Has built and supported production ML systems at scale. Architectural Leadership: You have experience leading architectural discussions, defining system design, and guiding technical decision-making. Inference & Training: Has trained or fine-tuned language models end-to-end; comfortable with deep learning, evaluation, and inference. Training capability: Has trained or fine-tuned language models end-to-end; comfortable with deep learning, evaluation, and inference. RAG & agents: Hands-on experience with LangChain / LangGraph and modern RAG patterns over structured and unstructured data. AI safety & authorization: Hands-on experience operating AI guardrails, scoped tool permissions, and authorization layers for production AI systems - especially in agentic contexts. Nice to Have Experience building ML systems for conversational AI, leasing, or CRM-adjacent workflows. GPU performance tuning (vLLM, TensorRT, Triton, or similar). Experience with ontology-driven systems or knowledge graphs supporting AI applications. Familiarity with real estate, property management, or leasing workflows. Contributions to open-source ML infrastructure or LLM tooling. Location Find out more about our locations by visiting our site. All late-stage candidates complete an in-person meeting with an AppFolian as part of our hiring process. Compensation & Benefits The compensation that we reasonably expect to pay for this role is: $200,000 - $275,000 base pay. The actual compensation for this role will be determined by a variety of factors, including but not limited to the candidate's skills, education, experience, and internal equity. Please note that compensation is just one aspect of a comprehensive Total Rewards package. The compensation range listed here does not include additional benefits or any discretionary bonuses you may be eligible for based on your role and/or employment type. Regular full-time employees are eligible for benefits - see here.

Job Description Job Description Hi, We're AppFolio We're innovators, changemakers, and collaborators. We're more than just a software company - we're building the AI-native platform where the real estate industry comes to do business. We're transforming property management: how properties are leased, how residents find their homes, and how intelligence flows across an entire portfolio. Realm-X is AppFolio's AI-native platform powering this transformation. Within it, Realm-X Leasing Performer is an autonomous AI agent that handles the end-to-end leasing lifecycle - lead management, tour scheduling, follow-up, application processing, etc. - on behalf of property managers and leasing teams. It's one of AppFolio's most ambitious bets on autonomous AI, and it needs ML engineering worthy of that ambition. Who We Are Looking For We're hiring a Staff Machine Learning Engineer to own the ML strategy and execution that makes the Realm-X Leasing Performer production-grade, observable, and continuously improving. You'll sit at the intersection of applied ML, agent systems, and leasing domain expertise - working directly with Leasing Engineering, Voice & Agents, and Research ML to translate prototypes into systems our customers can depend on every day. This isn't a platform-only role. You'll be close enough to the product to shape how the Leasing Performer reasons, acts, and learns - and close enough to infrastructure to make sure it's reliable, cost-efficient, and safe at scale. Your Impact Own the ML Strategy for Leasing: Define and drive the machine learning roadmap across Leasing products - identifying where ML creates the most leverage, making the right model and architecture bets, and working closely with Product and Engineering leadership to align the team around a coherent technical vision that reflects real customer outcomes. Drive the Development & Architecture for Autonomous AI Agents: Be the ML lead for AppFolio's autonomous leasing agent - shaping how it communicates with prospective tenants and helps streamline leasing operations. You'll own the model quality, evaluation framework, and continuous improvement loop that makes the Performer better over time. Translate Research into Product: Partner with Voice & Agents and Research ML to evaluate new capabilities - fine-tuning approaches, retrieval strategies, agentic patterns - and make the call on what's ready to ship and what needs more hardening before it reaches customers. Drive Model Quality and Evaluation: Build the evaluation and experimentation infrastructure that lets the Leasing team ship ML changes with confidence - defining what "better" looks like for leasing-specific tasks and owning the metrics that reflect real customer outcomes. Set the ML Bar for Leasing Engineering: Establish the patterns, standards, and practices that the broader Leasing Engineering team follows when integrating ML - from prompt engineering and RAG to fine-tuning and model selection. Be the person the team comes to when the ML question is hard. Operate with Production Discipline: Ensure that ML systems powering the Leasing Performer meet the reliability bar that production SaaS demands - SLOs, observability, cost discipline, and a clear on-call posture. You don't have to build all of it, but you own the outcomes. Qualifications Systems thinker: You think in terms of platforms and long-term leverage, not just features. You understand how ML infrastructure decisions compound over time. Production builder: You've built and scaled ML infrastructure in production with meaningful business impact - and you treat it like any other production system. Domain curiosity: You take time to understand the business workflows your systems serve - in this case, leasing - and use that understanding to make better technical bets. Ambiguity: You operate effectively in high ambiguity, turning unclear infra problems into clear direction. Owner-operator: You take ownership with a founder mindset, act with urgency, and focus on outcomes. Collaboration: You are humble, collaborative, and low-ego - you elevate those around you and work fluidly across ML, product, and engineering. Reliability mindset: You treat ML infra like any other production system: SLOs, on-call, observability, postmortems. Sustainability: You value work-life balance as a foundation for sustained high performance. Must Have ML Development at scale: Has built and supported production ML systems at scale. Architectural Leadership: You have experience leading architectural discussions, defining system design, and guiding technical decision-making. Inference & Training: Has trained or fine-tuned language models end-to-end; comfortable with deep learning, evaluation, and inference. Training capability: Has trained or fine-tuned language models end-to-end; comfortable with deep learning, evaluation, and inference. RAG & agents: Hands-on experience with LangChain / LangGraph and modern RAG patterns over structured and unstructured data. AI safety & authorization: Hands-on experience operating AI guardrails, scoped tool permissions, and authorization layers for production AI systems - especially in agentic contexts. Nice to Have Experience building ML systems for conversational AI, leasing, or CRM-adjacent workflows. GPU performance tuning (vLLM, TensorRT, Triton, or similar). Experience with ontology-driven systems or knowledge graphs supporting AI applications. Familiarity with real estate, property management, or leasing workflows. Contributions to open-source ML infrastructure or LLM tooling. Location Find out more about our locations by visiting our site. All late-stage candidates complete an in-person meeting with an AppFolian as part of our hiring process. Compensation & Benefits The compensation that we reasonably expect to pay for this role is: $200,000 - $275,000 base pay. The actual compensation for this role will be determined by a variety of factors, including but not limited to the candidate's skills, education, experience, and internal equity. Please note that compensation is just one aspect of a comprehensive Total Rewards package. The compensation range listed here does not include additional benefits or any discretionary bonuses you may be eligible for based on your role and/or employment type. Regular full-time employees are eligible for benefits - see here.

Job Description Job Description Hi, We're AppFolio We're innovators, changemakers, and collaborators. We're more than just a software company - we're building the AI-native platform where the real estate industry comes to do business. We're transforming property management: how properties are leased, how residents find their homes, and how intelligence flows across an entire portfolio. Realm-X is AppFolio's AI-native platform powering this transformation. Within it, Realm-X Leasing Performer is an autonomous AI agent that handles the end-to-end leasing lifecycle - lead management, tour scheduling, follow-up, application processing, etc. - on behalf of property managers and leasing teams. It's one of AppFolio's most ambitious bets on autonomous AI, and it needs ML engineering worthy of that ambition. Who We Are Looking For We're hiring a Staff Machine Learning Engineer to own the ML strategy and execution that makes the Realm-X Leasing Performer production-grade, observable, and continuously improving. You'll sit at the intersection of applied ML, agent systems, and leasing domain expertise - working directly with Leasing Engineering, Voice & Agents, and Research ML to translate prototypes into systems our customers can depend on every day. This isn't a platform-only role. You'll be close enough to the product to shape how the Leasing Performer reasons, acts, and learns - and close enough to infrastructure to make sure it's reliable, cost-efficient, and safe at scale. Your Impact Own the ML Strategy for Leasing: Define and drive the machine learning roadmap across Leasing products - identifying where ML creates the most leverage, making the right model and architecture bets, and working closely with Product and Engineering leadership to align the team around a coherent technical vision that reflects real customer outcomes. Drive the Development & Architecture for Autonomous AI Agents: Be the ML lead for AppFolio's autonomous leasing agent - shaping how it communicates with prospective tenants and helps streamline leasing operations. You'll own the model quality, evaluation framework, and continuous improvement loop that makes the Performer better over time. Translate Research into Product: Partner with Voice & Agents and Research ML to evaluate new capabilities - fine-tuning approaches, retrieval strategies, agentic patterns - and make the call on what's ready to ship and what needs more hardening before it reaches customers. Drive Model Quality and Evaluation: Build the evaluation and experimentation infrastructure that lets the Leasing team ship ML changes with confidence - defining what "better" looks like for leasing-specific tasks and owning the metrics that reflect real customer outcomes. Set the ML Bar for Leasing Engineering: Establish the patterns, standards, and practices that the broader Leasing Engineering team follows when integrating ML - from prompt engineering and RAG to fine-tuning and model selection. Be the person the team comes to when the ML question is hard. Operate with Production Discipline: Ensure that ML systems powering the Leasing Performer meet the reliability bar that production SaaS demands - SLOs, observability, cost discipline, and a clear on-call posture. You don't have to build all of it, but you own the outcomes. Qualifications Systems thinker: You think in terms of platforms and long-term leverage, not just features. You understand how ML infrastructure decisions compound over time. Production builder: You've built and scaled ML infrastructure in production with meaningful business impact - and you treat it like any other production system. Domain curiosity: You take time to understand the business workflows your systems serve - in this case, leasing - and use that understanding to make better technical bets. Ambiguity: You operate effectively in high ambiguity, turning unclear infra problems into clear direction. Owner-operator: You take ownership with a founder mindset, act with urgency, and focus on outcomes. Collaboration: You are humble, collaborative, and low-ego - you elevate those around you and work fluidly across ML, product, and engineering. Reliability mindset: You treat ML infra like any other production system: SLOs, on-call, observability, postmortems. Sustainability: You value work-life balance as a foundation for sustained high performance. Must Have ML Development at scale: Has built and supported production ML systems at scale. Architectural Leadership: You have experience leading architectural discussions, defining system design, and guiding technical decision-making. Inference & Training: Has trained or fine-tuned language models end-to-end; comfortable with deep learning, evaluation, and inference. Training capability: Has trained or fine-tuned language models end-to-end; comfortable with deep learning, evaluation, and inference. RAG & agents: Hands-on experience with LangChain / LangGraph and modern RAG patterns over structured and unstructured data. AI safety & authorization: Hands-on experience operating AI guardrails, scoped tool permissions, and authorization layers for production AI systems - especially in agentic contexts. Nice to Have Experience building ML systems for conversational AI, leasing, or CRM-adjacent workflows. GPU performance tuning (vLLM, TensorRT, Triton, or similar). Experience with ontology-driven systems or knowledge graphs supporting AI applications. Familiarity with real estate, property management, or leasing workflows. Contributions to open-source ML infrastructure or LLM tooling. Location Find out more about our locations by visiting our site. All late-stage candidates complete an in-person meeting with an AppFolian as part of our hiring process. Compensation & Benefits The compensation that we reasonably expect to pay for this role is: $200,000 - $275,000 base pay. The actual compensation for this role will be determined by a variety of factors, including but not limited to the candidate's skills, education, experience, and internal equity. Please note that compensation is just one aspect of a comprehensive Total Rewards package. The compensation range listed here does not include additional benefits or any discretionary bonuses you may be eligible for based on your role and/or employment type. Regular full-time employees are eligible for benefits - see here.

Job Description Job Description Software Packaging Engineer 6 month+ Contract Hybrid, 3 days/week onsite in Vienna, VA W2 Hourly Rate: $60/hr. range Description We are seeking an experienced Software Packaging Engineer contractor to support our client's EUC Software Delivery Enhancements Project, a strategic initiative focused on modernizing software packaging and application delivery across the enterprise. The primary objective of this role is to assess, package, test, and deploy our existing portfolio of enterprise applications using Liquidware FlexApp application layering technology. The engineer will work closely with End User Computing (EUC), Engineering, Infrastructure, Security, and Business stakeholders to transform traditionally installed applications into virtualized FlexApp packages that improve application delivery, reduce operational complexity, and support both Virtual Desktop Infrastructure (VDI) and physical Windows environments. This position requires extensive experience in software packaging, application deployment, troubleshooting, and lifecycle management, with a strong preference for candidates who have experience with Liquidware FlexApp application layering. Responsibilities Software Packaging & FlexApp Migration Application Testing & Validation Software Deployment & Administration Engineering & Operational Support Required Qualifications 3+ years of Software Packaging Engineering experience Experience packaging enterprise software in Windows environments Strong knowledge of MSI packaging, application repackaging, and deployment technologies Experience with Microsoft Endpoint Configuration Manager (MECM) Proficiency with PowerShell scripting and application automation Experience troubleshooting application installation and compatibility issues Familiarity with application lifecycle management and software delivery processes Strong analytical and problem-solving skills Excellent communication and technical documentation skills Ability to work independently and collaboratively across multiple technical teams Preferred Qualifications Experience creating and managing FlexApp virtualized apps and packaging workflows Experience supporting Virtual Desktop Infrastructure (VDI) environments Experience with application virtualization and layering technologies Experience with InstallShield or similar packaging tools Familiarity with profile management and user environment management solutions Experience with Splunk, UberAgent, or endpoint monitoring tools Experience with software delivery modernization initiatives System One, and its subsidiaries including Joulé and Mountain Ltd., are leaders in delivering outsourced services and workforce solutions across North America. We help clients get work done more efficiently and economically, without compromising quality. System One not only serves as a valued partner for our clients, but we offer eligible employees health and welfare benefits coverage options including medical, dental, vision, spending accounts, life insurance, voluntary plans, as well as participation in a 401(k) plan. System One is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, age, national origin, disability, family care or medical leave status, genetic information, veteran status, marital status, or any other characteristic protected by applicable federal, state, or local law. Ref:

Job Description Job Description Design Expert Job Type: Contractor Location: Remote Schedule: Flexible / Self-Directed Job Overview We are seeking senior Product Design and AI-Assisted Development Experts to create evaluation tasks for AI systems working across rapid prototyping, product design, and human-AI collaboration. Experts may contribute to either or both tracks: Vibecoding: AI-assisted software development, natural-language-to-code workflows, and rapid prototyping. Design: Product design, UX/UI, design systems, component libraries, research, and usability. No formal credential is required; demonstrated expertise and shipped work are highly valued. Key Responsibilities Create realistic scenarios covering rapid prototyping, iteration, design systems, and product-design-engineering collaboration . Develop tasks involving AI coding tools such as Cursor, Claude Code, v0, and Replit . Create Design-track tasks using Figma, Framer, prototyping tools, and design-system platforms . Apply prompt-driven development, human-centered design, heuristic evaluation, and rapid prototyping methodologies. Produce reference prototypes, code artifacts, design specifications, and usability evaluation reports. Develop detailed rubrics that distinguish senior-level product judgment from generic or template-driven work. Collaborate on task refinement and evaluation standards. Required Skills Product Design UX/UI Design Rapid Prototyping Design Systems Vibecoding / AI-Assisted Development Human-Centered Design User Research & Usability Testing Figma / Prototyping Tools Design Critique Product Judgment AI-Assisted Coding Evaluation & Rubric Development Preferred Qualifications 5+ years of experience as a product designer, design lead, or AI-native engineer/vibecoder. Experience at a product- or design-focused company, startup, or notable independent product. Direct ownership of shipped product designs, design systems, or AI-assisted development workflows . Strong fluency with relevant design or AI development tools. Portfolio of shipped work strongly preferred. Experience creating rubrics, training materials, design critiques, or evaluation frameworks is a plus. Contract & Payment Independent contractor engagement. Fully remote with a flexible schedule. Project duration may vary based on business needs and performance. Weekly payments via Stripe or Wise based on services rendered. Screening Questions How many years of product design, UX/UI, or AI-assisted development experience do you have? Which track do you specialize in: Vibecoding, Design, or both ? What products, design systems, or AI-assisted workflows have you shipped? Which tools do you use regularly (e.g., Figma, Framer, Cursor, Claude Code, v0, Replit)? Do you have a portfolio of shipped work? What experience do you have creating design critiques, rubrics, or evaluation frameworks? How soon can you start?

Job Description Job Description Network Security Systems Manager - Q Clearance Required Summary: We are seeking an experienced Network Security Systems Manager to lead the administration, security, and operations of network security systems supporting LAN/WAN environments. The ideal candidate will have extensive experience managing enterprise network security infrastructure, leading technical security teams, and implementing security policies, controls, and best practices. This role requires strong technical judgment, leadership skills, and the ability to plan, prioritize, and execute network security initiatives in a complex government environment. Location: Washington, DC or Gaithersburg, MD Salary: Up to $178,000 Clearance: Active Q Clearance Required Education: Bachelor's degree from an accredited university or college in Information Technology with an emphasis in Cybersecurity or Information Assurance, Computer Science, or a related field. Required Certifications: One or more of the following certifications or equivalent: GIAC Information Security Professional (GISP) ISC2 Certified Information Systems Security Professional (CISSP) GIAC Security Essentials (GSEC) Experience: Minimum of five (5) years of experience managing network security systems in LAN/WAN environments. Experience leading network security administration staff and technical teams. Experience managing enterprise network security infrastructure, systems, and technologies. Broad knowledge of network security concepts, practices, principles, and procedures. Experience planning, implementing, and maintaining network security solutions. Experience identifying and addressing network security risks, vulnerabilities, and operational issues. Ability to apply extensive technical experience and sound judgment to plan and accomplish organizational goals. Experience developing and implementing security policies, procedures, standards, and controls. Strong understanding of network security architecture, access controls, firewalls, intrusion detection/prevention, VPNs, and secure network communications. Experience supporting security monitoring, incident response, vulnerability management, and network security assessments. Ability to lead technical teams, prioritize workload, manage competing requirements, and communicate effectively with technical and management stakeholders. Preferred Certifications: Certified Information Security Manager (CISM) ISC2 Certified Cloud Security Professional (CCSP) GIAC Network Forensic Analyst (GNFA) GIAC Certified Intrusion Analyst (GCIA) GIAC Certified Incident Handler (GCIH) GIAC Certified Firewall Analyst (GCFW) Cisco Certified Network Professional - Security (CCNP Security) Fortinet Certified Professional or equivalent Fortinet certification Palo Alto Networks Certified Network Security Engineer (PCNSE) or equivalent CompTIA Security+ CompTIA CySA+ ISACA Certified in Risk and Information Systems Control (CRISC) Certified Ethical Hacker (CEH) Juniper Networks security certification or equivalent ActioNet is a CMMI-DEV Level 4, CMMI-SVC Level 4, ISO 20000, ISO 27001, ISO 9001, HDI-certified, woman-owned IT Solutions Provider with strong qualifications and expertise in Agile Software Engineering, Cloud Solutions, Cyber Security and IT Managed Services. With 24+ years of stellar past performance, ActioNet is the premier Trusted Innogrator! Why ActioNet? At ActioNet, our Passion for Quality is at the heart of everything we do: We are committed to make ActioNet a great place to work and continue to invest in our ActioNeters We are committed to our customers by driving and sustaining Service Delivery Excellence We are committed to give back to our Community, help others and make the world a better place for our next generation ActioNet is proud to be named as a Top Workplace for the ninth year in a row (2014 - 2022). We have 98% of Customer retention rate. We are passionate about the inspirational missions of our customers and we entrust our employees and teams to deliver exceptional performance to enable the safety, security, health and well-being of our nation. What's in It For You? As an ActioNeter, you get to be part of exceptional team and a corporate culture that nurtures mutual success for our customers, employees and our communities. We give you the tools to be successful; all you need to do is bring your best ideas, your energy and a desire to develop your skills, experience and career. Are you ready to make a difference? ActioNet is an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. Direct Applicants, only. No Agencies, No third-party recruiters, please

Job Description Job Description Here at Appian, our values of Intensity and Excellence define who we are. We set high standards and live up to them, ensuring that everything we do is done with care and quality. We approach every challenge with ambition and commitment, holding ourselves and each other accountable to achieve the best results. When you join Appian, you'll be part of a passionate team dedicated to accomplishing hard things, together. Principal ML Platform Engineer Location: Remote (US) Lead the engineering of software that matters - driving AI automation for the world's largest enterprises. About the Team Appian Engineering spans the full depth of our platform: from the foundational layers that power enterprise scale, to the AI capabilities redefining what automation can do. We operate in a highly collaborative, fast-paced environment focused on technical precision, continuous learning, and high code quality. By joining our team, you will solve real-world problems that directly shape how Appian delivers our AI-Powered Process Automation platform to enterprises around the world. The Opportunity As a Principal Software Engineer, you will serve as a technical linchpin for the team, bringing deep expertise in cloud-native architecture and a track record of influencing engineering direction beyond your immediate scope. Equipped with cutting-edge AI tooling, you will drive the design and delivery of high-complexity engineering solutions, set the technical bar for the team, and lead other engineers towards solutions of real complexity to ensure flawless Enterprise-Grade Orchestration. What You'll Do Develop Clean Software: Architect, build, and optimize high-performance software systems while maintaining a strong personal technical presence on the team. Lead Platform Modernization: Spearhead strategic technological changes and champion code refactoring efforts to keep the core Appian codebase cutting-edge, modern, and performant. Engineer with AI: Use AI coding tools fluently as a force multiplier: generating, reviewing, and critically evaluating AI-assisted code to ship faster without compromising quality or correctness. Lead Architecture & Delivery: Drive technical story breakdowns, acceptance criteria, and architectural design across complex, multi-tier application layers - from feature scoping through implementation. Optimize Performance & Scale: Manage product availability, latency, scalability, and efficiency by engineering deep reliability into our core software systems and performing advanced system tuning. Drive Engineering Excellence: Radiate development best practices across the department, perform meticulous code reviews on design and implementation, and build automation frameworks to prevent problem recurrence. Lead & Grow Engineers: Actively coach and mentor engineers at multiple levels, identify and close skill gaps on the team, and take ownership of accelerating the technical growth of those around you. Influence Technical Documentation: Share your expert domain knowledge regularly across the department, building a reputation as a vital resource and publishing high-quality content to Engineering's permanent documentation site. Required Qualifications Education: Minimum of a Bachelor of Science degree in Computer Science or a related technical/analytical discipline. (Equivalent experience is not accepted in lieu of a degree). Experience: 10+ years of relevant software development experience with a BS (or 8+ years of experience paired with a Master of Science in Computer Science or related field). Technical Mastery: Expert coding, scripting, and debugging proficiency in one or more core enterprise programming languages, specifically Java, Python, or Go. Domain Expertise: Deep working knowledge of distributed systems, cloud infrastructure, and the ability to contribute meaningfully at a senior individual contributor level within that space. Cross-Team Influence: Demonstrated ability to drive technical decisions and shape engineering practices beyond a single team or project scope. AI-Augmented Development: Demonstrated experience using AI coding assistants and a strong ability to evaluate, coach others on, and selectively apply AI-generated code in a production engineering context. Production Mastery: Proven experience developing, optimizing, and maintaining a high-volume, mission-critical production service environment. Communication & Alignment: Exceptional ability to communicate highly technical architectures verbally, visually, and in writing to diverse engineering audiences. Preferred Qualifications Cloud Architecture: Strong experience designing microservices, working with containerization (Docker, Kubernetes), and implementing modern CI/CD pipelines. Cloud Platforms: Deep experience developing and operating infrastructure across public cloud ecosystems, specifically AWS, Azure, and/or GCP. We value experience with enterprise platforms such as Salesforce or ServiceNow, as these skills translate well into our Enterprise-Grade Orchestration environment. What We Equip You With High-Impact Autonomy: A leadership environment where you will have real ownership over your team's direction, the latitude to make meaningful decisions, and participation in broader Engineering discussions. New Hire Orientation: A robust onboarding experience designed to integrate you smoothly into our technology, culture, and leadership model so you can show up for your team from day one. Continuous Enablement: Access to premier learning resources and dedicated learning time focused on both your continued technical growth and your evolution as an engineering leader. Sponsored Certifications: Full corporate sponsorship for professional technical certifications to advance your engineering credentials. The base salary range represents a good faith and reasonable estimate of the range at the time of posting. Actual compensation will be dependent on a number of factors including, but not limited to, the candidate's relevant work experience, qualifications, internal peer equity, and market and business conditions that exist when extending an offer. A discretionary bonus may be awarded in recognition of individual and company performance. In addition, Appian provides generous benefits offerings that include a 401(k) plan with company match, flexible time off, paid parental leave, medical, dental, and vision plans, life insurance, disability insurance, wellness programs, flexible spending accounts, health savings account contributions, an employee referral bonus program, and learning and development resources. Certain positions may be eligible for equity awards. Pay and benefits are subject to change at any time, consistent with the terms of any applicable compensation, commission, bonus, or benefit plans. Base Salary Range $175,000-$325,000 USD Tools and Resources Training and Development: During onboarding, we focus on equipping new hires with the skills and knowledge for success through department-specific training. Continuous learning is a central focus at Appian, with dedicated mentorship and the First-Friend program being widely utilized resources for new hires. Growth Opportunities: Appian provides a diverse array of growth and development opportunities, including our leadership program tailored for new and aspiring managers, a comprehensive library of specialized department training through Appian University, skills based training, and tuition reimbursement for those aiming to advance their education. This commitment ensures that employees have access to a holistic range of development opportunities. Community: We'll immerse you into our community rooted in respect starting on day one. Appian fosters inclusivity through our 8 employee-led affinity groups. These groups help employees build stronger internal and external networks by planning social, educational, and outreach activities to connect with Appianites and larger initiatives throughout the company. Benefits Appian offers a comprehensive benefits package designed to support your health, wellbeing, and financial future. Benefits may include health coverage, Employee Assistance Program (EAP) with free mental health support, life and disability insurance, an Employee Stock Purchase Program (ESPP), a retirement/pension plan, wellness dollars, tuition reimbursement, family-forming benefits and more. Benefits vary by country-please ask your Talent Acquisition contact for details specific to the location you are applying to. About Appian Appian provides AI automation for mission-critical work. We automate complex processes in large enterprises and governments. Our platform is known for its unique reliability and scale. We've been automating processes for more than 25 years and understand enterprise operations like no one else. For more information, visit Nasdaq: APPN Follow Appian: LinkedIn, Youtube, Instagram, Facebook Appian is an equal opportunity employer that strives to attract and retain the best talent . click apply for full job details

Job Description Job Description Job Title: AV Technician Location: Washington, DC Type: Contract Compensation: $36.80 Work Model: Onsite - onsite Hours: 40.0 Security Clearance: Ability to obtain and maintain SEC Public Trust (or higher if required) Responsibilities Proactively inspect, configure, and maintain AV/VTC equipment in meeting rooms, auditoriums, and multipurpose rooms. Manage deployment, setup, and relocation of AV/VTC components to support operational and event requirements. Troubleshoot front-end AV/VTC hardware and software issues and restore services with minimal disruption. Perform routine readiness checks to ensure monitors, microphones, conference phones, and related room systems remain fully operational. Provide user-facing support for collaboration tools, including Webex and Microsoft Teams. Field and resolve user questions on AV/VTC usage, meeting startup, content sharing, and audio/video performance. Support conference and hybrid meeting connectivity and coordinate escalations for unresolved issues. Communicate service updates and usage guidance to end users to improve collaboration outcomes. Support production of live events, including town halls, commission meetings, and other high-visibility sessions. Execute live video/audio support activities and assist with webcast or streaming operations. Coordinate with internal stakeholders and third-party providers for services such as captioning and interpretation support. Perform post-production editing for recorded events and deliver high-quality final media outputs. Conduct training sessions on selection, use, and design of audiovisual materials and presentation equipment. Develop manuals, workbooks, and user-facing reference materials to support AV/VTC operations. Create practical job aids for common room technologies and collaboration workflows. Capture recurring issues and recommend process improvements to strengthen AV/VTC service delivery. Requirements Minimum of 5 years of experience providing front-end AV/VTC support in enterprise or government environments. Hands-on experience managing, deploying, and troubleshooting AV/VTC equipment. Demonstrated skills and knowledge to operate AV/VTC systems, including live broadcasts and post-production editing. Education: Bachelor's degree in a relevant field (e.g., Information Technology, Computer Science, Engineering). Technical Skills: AV/VTC system operation and troubleshooting across conference rooms, auditoriums, and multipurpose spaces. Webex and Microsoft Teams support for meetings and collaboration. Live broadcast, streaming/webcast support, and post-production video editing. End-user training delivery and development of manuals, texts, and workbooks. Preventive AV equipment management, issue triage, and service restoration. System One, and its subsidiaries including Joulé and Mountain Ltd., are leaders in delivering outsourced services and workforce solutions across North America. We help clients get work done more efficiently and economically, without compromising quality. System One not only serves as a valued partner for our clients, but we offer eligible employees health and welfare benefits coverage options including medical, dental, vision, spending accounts, life insurance, voluntary plans, as well as participation in a 401(k) plan. System One is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, age, national origin, disability, family care or medical leave status, genetic information, veteran status, marital status, or any other characteristic protected by applicable federal, state, or local law. Ref:

Job Description Job Description Altamira brings a commercial mindset to solving the most complex national security problems by delivering mission application development, multi-intelligence analysis, and data science technologies and solutions to the defense, intelligence, and homeland security communities. Altamira's culture of innovation and excellence, and mid-market-size, positions us as the premier next generation leader bringing technology solutions to mission. Position Description We are seeking an experienced R&D Technical Lead to bridge the gap between AI/ML research and production-ready solutions. In this role, you will provide technical leadership across AI/ML and software engineering, guiding teams from early-stage research concepts through successful customer delivery. The ideal candidate brings a broad software engineering background combined with strong AI/ML expertise, with the ability to translate machine learning models and research into scalable, integrated software architectures. You will collaborate across disciplines to drive technical decisions, mentor development teams, and ensure solutions meet real-world customer needs. Our work focuses on applied AI/ML solutions for real-world object tracking, detection, and characterization, enabling advanced data triaging and system automation. These capabilities help our customers manage increasing volumes of data and address the challenges associated with data saturation. Core Responsibilities Team Leadership: Provide technical guidance to engineering teams, aligning project requirements to technical tasking System Architecture: Design and implement scalable, high-performance software systems that integrate AI/ML capabilities Collection Coordination: Architect multi-agent or agentic workflows to synchronize data collection efforts across various projects, optimizing resource allocation. Technical Mentorship: Lead a high-performing team of engineers, conducting code reviews and setting engineering standards for MLOps and production pipelines. Strategic Integration: Collaborate with project managers to translate complex client requirements into actionable AI/ML roadmaps. Qualifications & Skills Education: Bachelor's or above in Computer Science, AI, or a related quantitative field. Experience: 7+ years of professional experience in machine learning, with at least 3 years leading teams from research or prototyping through production deployment. Computer Vision Expertise: Proven track record in developing computer vision models for object tracking (e.g., CNNs, Transformers) and real-time video analytics. Advanced Programming: Expert-level proficiency in Python and high-performance languages (C++/Rust/Java) alongside familiarity with backend deployment tools (Docker, Kubernetes). Data Management: Experience overseeing the full data lifecycle, from acquisition and cleaning to high-fidelity labeling for specialized collections. Communication: Ability to articulate complex AI concepts to non-technical stakeholders and executive leadership.

Why USAA? At USAA, our mission is to empower our members to achieve financial security through highly competitive products, exceptional service and trusted advice. We seek to be the choice for the military community and their families. Embrace a fulfilling career at USAA, where our core values - honesty, integrity, loyalty and service - define how we treat each other and our members. Be part of what truly makes us special and impactful. We are proud to support active-duty military spouses. USAA roles may offer remote or hybrid flexibility for active-duty military spouses consistent with applicable policy and business needs. The Opportunity As a dedicated Senior Infrastructure Engineer - Data Protection, you will be responsible for designing, implementing, maintaining, and troubleshooting our data backup, recovery, and cyber resiliency solutions. This role is critical for ensuring business continuity, data integrity, and the protection of our organization's valuable information against data loss, system failures, and cyber threats. You will create, modify, maintain and support infrastructure system components that enable IT Services. You will balance availability, security, efficiency and functional requirements to help provide an optimized production service. You will also identify and manage existing and emerging risks that stem from business activities and ensure these risks are effectively identified and escalated to be measured, monitored and controlled. We offer a flexible work environment that requires an individual to be in the office 4 days per week. This position can be based in one of the following locations: San Antonio, TX, Plano, TX, Phoenix, AZ, Colorado Springs, CO, Charlotte, NC, or Tampa, FL. Relocation assistance is not available for this position. What you'll do: Drives data protection transformation initiatives focused on simplification, standardization, resilience, and operational efficiency, alongside developing engineering standards, implementation plans, and technical documentation. Architects and deploys data protection solutions for Virtual Hosts, SQL, NO-SQL, DB2, Oracle distributed workloads, as well as cloud (Azure and AWS), SaaS, and Active Directory workloads. Supports critical operational automation, requiring the development and implementation of Infrastructure-as-Code solutions, automated workflows, and process improvements to streamline operations and enhance deployment consistency. Maintains focus on regulatory compliance, business continuity, cyber resilience, and assurance of data integrity and immutability. Independently designs scalable IT system infrastructure, provides oversight and priority for system change - reserves execution for complex implementations, and automates service delivery and maintenance tasks; provides direction and priority for monitoring and tooling activities. Independently resolves highly complex technology production issues and leads troubleshooting of end-to-end solutions that span across multiple systems. Leads analysis of end-to-end system failures to identify opportunities across multiple systems. Makes recommendations to business leaders on process and business solution improvements. Independently experiments with new patterns and technologies. Helps establish and improve engineering best practices, concepts, and patterns with peers and the business. Understands the customer and proactively identifies innovative solutions and ideas for the product/business. Mentors' engineers, coach engineers on design, development, and maintenance of systems. Develop software defined infrastructure in code in CI/CD Pipelines. Ensures risks associated with business activities are effectively identified, measured, monitored, and controlled in accordance with risk and compliance policies and procedures. What you have: Education: Bachelor's degree; OR 4 years of relevant education and/or experience. 6 years of infrastructure experience demonstrating depth of technical understanding within a specific discipline(s)/technology(s) to include 2 years' experience in Systems Operations environment supporting complex environment deployment and infrastructure management activities or applicable IT experience such as IT Management, Software Development, Data Engineering, and Agile Product/Release Management. 4 years of experience in designing, implementing and maintaining data backup, recovery, and cyber resiliency infrastructure. Advanced level of business acumen in the areas of business operations, risk management, industry practices and emerging trends. Knowledge and proficient understanding of designing scalable IT system infrastructures, implementing system changes, or automating service delivery and maintenance tasks. Demonstrated experience working with cloud technologies and tools. Demonstrated experience working with image-based backup solutions, virtualized infrastructure, database backups, and disaster recovery. What sets you apart: Experience in developing, deploying and maintaining large scale backup/recovery solutions. Experience in implementing cyber recovery solutions that includes ability to detect and respond to threats and quickly restore operations. Experience developing and maintaining automated restore orchestration. Experience working in an environment with strict federal regulations and operational control standards designed to ensure business continuity, data integrity and privacy. Rubrik Certifications such as Rubrik Certified System Administrator (RCSA) and Rubrik Certified Cloud Specialist (RCCS) Automation experience with Ansible. US military experience gained through military service or gained as a military spouse / domestic partner. Compensation range: The salary range for this position is: $114,080 - $218,030. USAA does not provide visa sponsorship for this role. Please do not apply for this role if at any time (now or in the future) you will need immigration support (i.e., H-1B, TN, STEM OPT Training Plans, etc.). Compensation: USAA has an effective process for assessing market data and establishing ranges to ensure we remain competitive. You are paid within the salary range based on your experience and market data of the position. The actual salary for this role may vary by location. Employees may be eligible for pay incentives based on overall corporate and individual performance and at the discretion of the USAA Board of Directors. The above description reflects the details considered necessary to describe the principal functions of the job and should not be construed as a detailed description of all the work requirements that may be performed in the job. Benefits: At USAA our employees enjoy best-in-class benefits to support their physical, financial, and emotional wellness. These benefits include comprehensive medical, dental and vision plans, 401(k), pension, life insurance, parental benefits, adoption assistance, paid time off program with paid holidays plus 16 paid volunteer hours, and various wellness programs. Additionally, our career path planning and continuing education assists employees with their professional goals. For more details on our outstanding benefits, visit our benefits page on Applications for this position are accepted on an ongoing basis, this posting will remain open until the position is filled. Thus, interested candidates are encouraged to apply the same day they view this posting. USAA is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

Why USAA? At USAA, our mission is to empower our members to achieve financial security through highly competitive products, exceptional service and trusted advice. We seek to be the choice for the military community and their families. Embrace a fulfilling career at USAA, where our core values - honesty, integrity, loyalty and service - define how we treat each other and our members. Be part of what truly makes us special and impactful. We are proud to support active-duty military spouses. USAA roles may offer remote or hybrid flexibility for active-duty military spouses consistent with applicable policy and business needs. The Opportunity As a dedicated Infrastructure Engineer I - Data Protection, you will be responsible for designing, implementing, maintaining, and troubleshooting our data backup, recovery, and cyber resiliency solutions. This role is critical for ensuring business continuity, data integrity, and the protection of our organization's valuable information against data loss, system failures, and cyber threats. You will create, modify, maintain and support infrastructure system components and solutions that enable business functions and IT Services. You will balance availability, security, efficiency and functional requirements to help provide an optimized production service. You will also identify and manage existing and emerging risks that stem from business activities and ensure these risks are effectively identified and escalated to be measured, monitored and controlled. We offer a flexible work environment that requires an individual to be in the office 4 days per week. This position can be based in one of the following locations: San Antonio, TX, Plano, TX, Phoenix, AZ, Colorado Springs, CO, Charlotte, NC, or Tampa, FL. Relocation assistance is not available for this position. What you'll do: Participates in data protection transformation initiatives focused on simplification, standardization, resilience, and operational efficiency, alongside developing engineering standards, implementation plans, and technical documentation. Deploys and maintains data protection solutions for Virtual Hosts, SQL, NO-SQL, DB2, Oracle distributed workloads, as well as cloud (Azure and AWS), SaaS, and Active Directory workloads. Supports critical operational automation, requiring the development and implementation of Infrastructure-as-Code solutions, automated workflows, and process improvements to streamline operations and enhance deployment consistency. Maintains focus on regulatory compliance, business continuity, cyber resilience, and assurance of data integrity and immutability. Under limited supervision, designs scalable IT system infrastructure, implements system changes with consistency and autonomy, and automates service delivery and maintenance tasks; builds monitoring and tooling for systems. Independently resolves complex technology production issues by troubleshooting IT systems. Identifies opportunities for improvements and makes recommendations to management. Analyzes complex outages and identifies opportunities for system improvements. Understands and consistently exercises engineering best practices, concepts, and patterns. Understands the customer and identifies solutions and ideas for the customer with some assistance. Evaluates potential Technology solutions with some oversight. Mentors junior engineers and may being mentoring peer engineers. Develop software defined infrastructure in code in CI/CD Pipelines. Ensures risks associated with business activities are effectively identified, measured, monitored, and controlled in accordance with risk and compliance policies and procedures. What you have: Bachelor's degree; OR 4 years of relevant education and/or experience 4 years of infrastructure experience demonstrating depth of technical understanding within a specific discipline(s)/technology(s) or applicable IT experience such as IT Management, Software Development, Data Engineering, and Agile Product/Release Management. 2 years of experience in developing, deploying and maintaining large scale backup/recovery solutions. Proficient level of business acumen in the areas of business operations, risk management, industry practices and emerging trends. Knowledge and understanding of designing scalable IT system infrastructures, implementing system changes, or automating service delivery and maintenance tasks. Basic understanding of cloud technologies and tools. Demonstrated experience working with image-based backup solutions, virtualized infrastructure, database backups, and disaster recovery. What sets you apart: Experience in developing, deploying and maintaining large scale backup/recovery solutions. Experience in implementing cyber recovery solutions that includes ability to detect and respond to threats and quickly restore operations. Experience developing and maintaining automated restore orchestration. Experience working in an environment with strict federal regulations and operational control standards designed to ensure business continuity, data integrity and privacy. Rubrik Certifications such as Rubrik Certified System Administrator (RCSA) and Rubrik Certified Cloud Specialist (RCCS) Automation experience with Ansible. US military experience gained through military service or gained as a military spouse / domestic partner. Compensation range: The salary range for this position is: $93,770 - $179,240. USAA does not provide visa sponsorship for this role. Please do not apply for this role if at any time (now or in the future) you will need immigration support (i.e., H-1B, TN, STEM OPT Training Plans, etc.). Compensation: USAA has an effective process for assessing market data and establishing ranges to ensure we remain competitive. You are paid within the salary range based on your experience and market data of the position. The actual salary for this role may vary by location. Employees may be eligible for pay incentives based on overall corporate and individual performance and at the discretion of the USAA Board of Directors. The above description reflects the details considered necessary to describe the principal functions of the job and should not be construed as a detailed description of all the work requirements that may be performed in the job. Benefits: At USAA our employees enjoy best-in-class benefits to support their physical, financial, and emotional wellness. These benefits include comprehensive medical, dental and vision plans, 401(k), pension, life insurance, parental benefits, adoption assistance, paid time off program with paid holidays plus 16 paid volunteer hours, and various wellness programs. Additionally, our career path planning and continuing education assists employees with their professional goals. For more details on our outstanding benefits, visit our benefits page on Applications for this position are accepted on an ongoing basis, this posting will remain open until the position is filled. Thus, interested candidates are encouraged to apply the same day they view this posting. USAA is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.