hatch I.T.

• Lead the technical architecture and implementation of an edge-native intelligent processing platform supporting distributed sensing, edge inference, and resilient mission operations. • Design scalable software architectures supporting heterogeneous edge computing devices, software-defined radios, embedded compute platforms, and cloud-enabled mission services. • Develop high-performance backend services using Python, FastAPI, asynchronous programming, and modern distributed software engineering techniques. • Lead integration of Software Defined Radio (SDR) platforms (such as Ettus USRP, GNU Radio, or equivalent SDR ecosystems) into software pipelines for real-time data processing and analytics. • Design resilient distributed processing frameworks capable of operating under degraded, disconnected, intermittent, and bandwidth-constrained communications. • Develop intelligent data processing pipelines that reduce communication overhead through feature extraction, prioritization, and adaptive data management. • Design peer-to-peer communication services supporting decentralized collaboration across heterogeneous edge devices. • Implement secure synchronization, workload distribution, and fault-tolerant processing across multiple edge computing nodes. • Lead software integration across embedded Linux systems, containerized services, edge compute devices, and cloud infrastructure. • Establish software architecture standards, CI/CD pipelines, testing frameworks, DevSecOps practices, and engineering best practices. • Collaborate closely with AI engineers to integrate machine learning inference capabilities into production software. • Produce technical documentation, software architecture artifacts, interface specifications, and engineering design documentation. • Support technical demonstrations, customer engagements, and prototype evaluations. • Mentor junior engineers while maintaining significant hands-on software development responsibilities.

• Contribute to the design and evolution of Expression's Agentic AI platform by defining scalable architectures for enterprise AI applications and services, including system architecture, core platform components, tooling, automation, coding standards, and platform performance, scalability, and reliability. • Architect, deliver, and optimize production-grade LLM services, agent workflows, orchestration layers, retrieval pipelines, and vector search technologies. • Provide technical leadership and mentorship: guide architecture and design reviews, grow engineers, and raise the bar for engineering quality and technical decision-making across the team. • Develop high-performance Python APIs and scalable backend services using FastAPI, asynchronous programming techniques, and modern software engineering practices. Set the technical direction and engineering standards for high-performance, scalable backend services and APIs, and champion modern software engineering best practices across the team. • Build and maintain the underlying AI platform that supports secure, observable, resilient, and production-ready AI workloads. • Design and implement AI governance capabilities, including guardrails, policy enforcement, model lifecycle management, responsible AI practices, and compliance with federal security and governance requirements. • Develop automated testing and evaluation strategies for AI-enabled applications, including prompt evaluation, model evaluation, regression testing, integration testing, and quality assurance. • Implement LLM observability, monitoring, logging, telemetry, performance metrics, and resilience strategies to ensure reliable production operation. • Design, implement, and maintain CI/CD pipelines and deployment automationDefine and drive CI/CD and deployment automation strategy to support secure, efficient delivery of AI services. • Collaborate with Product, UX, Infrastructure, Security, and other cross-functional teams to continuously improve platform capabilities and deliver customer-focused solutions. • Collaborate with clients, lead product demonstrations, and communicate technical concepts and platform capabilities to both technical and executive audiences. • Produce clear technical documentation, architecture diagrams, design proposals, and other engineering artifacts.

• Design and implement AI capabilities supporting intelligent data characterization, classification, prioritization, and decision support. • Evaluate, optimize, and deploy open-weight foundation models appropriate for resource-constrained edge environments. • Develop efficient inference pipelines supporting heterogeneous compute environments ranging from embedded processors to workstation-class systems. • Implement Retrieval-Augmented Generation (RAG), semantic search, and knowledge retrieval capabilities where appropriate. • Design AI orchestration workflows supporting distributed inference across multiple edge devices. • Develop evaluation methodologies for AI accuracy, latency, resource utilization, and operational performance. • Implement model monitoring, observability, testing, and automated evaluation frameworks. • Collaborate with software engineers to integrate AI models into production software platforms. • Optimize models using quantization, pruning, distillation deployment technologies. • Support experimentation involving multimodal data sources, sensor-derived features, and structured mission data. • Develop AI governance practices including model evaluation, explainability, responsible AI, and secure deployment. • Document model development, evaluation results, and technical recommendations. • Support customer demonstrations and prototype evaluations.

• Technical discovery and product demos tailored to CISOs, security teams, HR leaders, and executive stakeholders • Security assessment questionnaires and RFP/RFI responses (with an AI-assisted workflow already in place) • Technical collateral: demo environments, battle cards, and solution briefs • The SE playbook itself — processes, tooling, and eventually the team

• Manage and grow an assigned book of business while conducting active new account prospecting and acquisition. • Conduct daily outbound phone prospecting as a core and non-negotiable part of the role. • Follow up on conference connections, networking activity, referrals, and event leads consistently and promptly. • Attend industry conferences, government procurement events, and networking functions regularly as a primary business development strategy. • Hunt for new sales opportunities within assigned territories, markets, and professional networks. • Develop and execute a territory sales plan covering priority prospects, procurement pathways, budget cycles, and decision-makers. • Serve as the primary sales relationship owner for all assigned accounts. • Identify cross-sell and upsell opportunities across Assura’s full service portfolio. • Meet assigned quarterly and annual sales goals, with a standard planning target of $1,000,000 annually. • Maintain complete and accurate records in HubSpot for all accounts, prospects, opportunities, proposals, contracts, and renewals. • Complete all assigned onboarding and ongoing sales training. • Collaborate with Marketing to develop and refine sales materials, outreach campaigns, and event collateral.

• This role is an excellent opportunity for someone passionate about helping organizations transform their ways of working to an agile state and who wants to help other teams implement an agile mindset and culture. • You will learn about your client's products, processes, and tools, and help identify areas for improvement that enable them to meet their goals. • Leveraging your expertise, you will help guide your clients toward good agile and SAFe practices and recommend processes and tools to support their journey. • As a Product Coach at Packaged Agile, you'll be responsible for helping your client understand how to build and lead a product culture that focuses on creating valuable and viable solutions. • Solve complex problems using sound logic and compelling narratives. • Advise on agile, SAFe, and Scrum @ Scale strategies to implement across the organization. • Build trust and collaborative relationships among all stakeholders across the ART. • Mentor Scrum Masters, leadership, PO/PMs, and other ART team members on agile and SAFe best practices. • Facilitate the identification of objectives and key results (OKRs) that are product-team specific, but roll up to organizational goals. • Coach clients on agile principles and processes and on building compelling Product Vision and Product Strategy descriptions and how to orient Product Roadmaps around the delivery of customer value as opposed to output. • Partner with teams and stakeholders to help improve their agile practices. • Identify practical ways to keep team members engaged and motivated in a remote environment. • Escalate impediments and risks, and clearly explain their impact in plain language.

• Help design, build, and scale cloud infrastructure • Support mission-critical systems • Work closely with other Cloud Engineers to maintain infrastructure • Drive cloud architecture decisions • Lead initiatives to improve reliability and scalability of applications

• Lead and scale a high-performing engineering and DevOps team • Responsible for hands-on development, deployment, and maintenance of software applications and infrastructure • Ensure continuous integration and continuous delivery (CI/CD) pipelines are robust, optimized, and automated • Write clean, maintainable, and efficient code, following best practices in software engineering and design patterns • Conduct code reviews and mentor junior engineers to ensure code quality and technical excellence • Optimize and manage cloud-based infrastructure on platforms like AWS, and/or Azure, ensuring high availability and scalability • Implement and manage monitoring, alerting, and logging systems to proactively detect and address application and performance issues

• Provide CISO-level advisory guidance to Assura clients • Oversee and mentor Virtual ISOs (VISOs) delivering day-to-day GRC work • Review deliverables for accuracy, completeness, and real-world applicability • Act as a senior escalation point for complex client questions • Translate regulatory and technical requirements into clear, practical guidance • Support scope expansion conversations when new client needs emerge • Help evolve Assura’s GRC methodologies, templates, and service offerings

• Ensure high availability, scalability, and performance of production systems. • Implement and maintain SLIs, SLOs, and SLAs for critical services. • Conduct capacity planning and performance tuning. • Automate infrastructure provisioning using IaC tools such as Terraform and Terragrunt, ansible. • Develop automation to minimize manual operations and improve deployment workflows. • Build CI/CD pipelines to support rapid and reliable deployments. • Design and maintain monitoring, logging, and alerting systems (Datadog). • Participate in on-call rotations and lead incident response efforts. • Perform root-cause analysis and develop postmortems to prevent recurring issues. • Manage cloud infrastructure (AWS, Azure) and container orchestration platforms (Kubernetes, ECS). • Optimize system architecture for reliability and fault tolerance. • Implement best practices for security, networking, and service resilience. • Work closely with development teams to design reliable microservices and distributed systems. • Advocate for SRE principles and drive operational excellence across engineering teams. • Mentor engineers on reliability practices, tooling, and automation strategies.