• Implement and maintain clean, well-tested code for MCP tools, agentic features, and their supporting services (front-end and back-end), to team standards • Integrate LLMs and models via APIs/SDKs to deliver agentic workflows, with attention to correctness, latency, and cost • Help build the guardrails of agentic workflows — human-in-the-loop steps, traceability, and clear error handling • Contribute to automated tests, evaluation harnesses for AI behavior, CI/CD pipelines, and developer tooling • Debug and troubleshoot across the stack (agent/tool logic, APIs, web UI), collaborating with senior engineers and QA • Work with Product and UX to translate requirements into technical tasks; surface risks and blockers early and seek mentorship

• Architect the project's technical foundation, ensuring scalable, secure and observable environments. • Combine Kubernetes, automation, proactive security and FinOps to support our services. • Design, implement and evolve cloud and Kubernetes environments for running applications, APIs, agents, AI services and data pipelines. • Build and maintain CI/CD pipelines, focusing on security, standardization, traceability and delivery speed. • Automate infrastructure provisioning using Infrastructure as Code practices. • Implement observability standards, including logs, metrics, tracing, dashboards, alerts and platform health indicators. • Support the operation of AI workloads, including inference services, embeddings, agent orchestration and integration components. • Ensure best practices for security, environment segregation, secrets management, access control and infrastructure policies. • Work on performance, availability, scalability, resilience and cost optimization. • Create reusable patterns for environments, deployments, monitoring, security and operations. • Work closely with AI, Data, Product, Full Stack and Machine Learning teams to translate technical needs into platform capabilities.

Role Description ASG is looking for an AI Systems Engineer to own and scale the AI ecosystem across HoldCo and its portfolio companies. This is a hands-on builder role for someone who thrives at the intersection of AI workflow automation, enterprise integrations, and practical security architecture. This person will be the primary operator responsible for deploying AI tools safely, building agentic workflows that drive real productivity, connecting enterprise systems through integrations, and making sure the whole environment is governed and secure. You're Excited About This Opportunity Because You Will: - Design, build, and deploy AI-powered workflows and agentic systems that automate high-value business processes across ASG and its portfolio companies. - Own the AI SaaS ecosystem end-to-end - from tool evaluation and vendor selection to configuration, cost management, and ROI measurement. - Architect secure, governed patterns for AI tool usage across the enterprise, including data handling, connector security, access controls, and LLM-specific risk management. - Build and manage identity and access management across the organization, designing secure, least-privilege architectures that scale across multiple companies. - Partner with AI Governance and business leaders to define safe usage policies, translate security concepts into practical guidance, and drive adoption without slowing the business down. - Enable and educate teams across ASG and its portfolio on effective, secure use of AI tools - building a culture of self-service and responsible usage. - Evaluate emerging AI capabilities and tooling continuously, and bring the best ideas into production quickly. Qualifications - You have hands-on experience building AI workflows, agentic systems, or multi-step automations in real production environments - not just experimenting in sandboxes. - You have connected enterprise systems using APIs, workflow automation platforms, or SaaS-native integrations, and you understand how data and permissions move between systems. - You think about security as a builder, not a gatekeeper - you design practical guardrails that protect the business without blocking it. - You've worked with enterprise AI platforms (Claude Enterprise, ChatGPT Enterprise, AWS Bedrock, Azure OpenAI) and orchestration tools (LangChain, LangGraph, CrewAI, MCP), and you understand IAM, data leakage risks, and connector security in enterprise environments. - You communicate clearly across technical and non-technical audiences — you can explain architecture decisions to a CISO and onboarding workflows to an HR team. - You've worked in small, scrappy environments where you owned everything and figured things out without a large team behind you. - You possess a proactive, solution-oriented, problem-solving mindset -- "I'll figure it out." - You thrive in a small, growing, fast-paced, results-oriented environment. Requirements - Base Salary Range: The target salary range for this position is ($150,000 – $200,000), and is part of a competitive total rewards package including an annual bonus, employer-paid benefits, L&D stipend and incentive pay for eligible roles. - Individual pay may vary from the target range and is determined by a number of factors including experience, location, internal pay equity, and other relevant business considerations. - We review all employee pay and compensation programs annually at minimum to ensure competitive and fair pay. Location - Fully remote. Open to candidates located anywhere in the U.S. - Hybrid is optional for candidates based in the San Francisco Bay Area. A Secure Candidate Experience All official emails and messages regarding opportunities at ASG, LLC, will come from our alpinesg.com email domain. Please be wary of communications from similar domains that may contain misspellings or slight variations. These could be attempts at phishing or impersonation. ASG will never ask you for sensitive personal information during the hiring process such as social security numbers, banking information or other personal details.

Role Description - Lead the deployment, integration, and operational support of AI platforms, tools, and services, ensuring compatibility with existing systems and enterprise processes. - Design, implement, monitor, and optimize AI infrastructure, working with server, cloud, and platform engineering teams. - Operationalize machine learning workflows and support AI-enabled applications from development through production deployment and sustainment. - Build and maintain CI/CD and MLOps pipelines for model packaging, testing, deployment, rollback, and lifecycle management. - Implement infrastructure automation using scripting, Infrastructure as Code, and configuration management practices. - Provide ongoing technical support, troubleshooting, root cause analysis, and documentation for AI platforms and user-facing AI services. - Maintain observability across AI systems through logging, metrics, performance monitoring, alerting, and incident response practices. - Ensure security, compliance, and governance requirements are met, including participation in audits, vulnerability management, and secure architecture reviews. - Assess and implement system enhancements to improve performance, scalability, reliability, and cost efficiency. - Collaborate across divisions to support diverse AI initiatives and align technical implementations with mission and business objectives. - Evaluate emerging AI tools, frameworks, and infrastructure approaches for operational fit, supportability, and long-term value. - Develop and maintain technical documentation, runbooks, architecture diagrams, and operational procedures. Qualifications - Bachelor’s degree in computer science, Engineering, Information Technology, or a related STEM field with 8-10 years of engineering experience. - 2+ years of experience supporting AI/ML platforms, MLOps workflows, model deployment, or AI-enabled infrastructure. - Strong coding and automation skills in Python, Bash, or similar scripting languages. - Experience with AI/ML frameworks and tooling such as PyTorch, Hugging Face, or similar ecosystems. - Proficiency with DevOps and MLOps practices, including CI/CD pipelines, Git-based workflows, containerization, and Kubernetes. - Experience deploying AI/ML models or AI services into operational environments, including containerized, cloud, or high-performance computing environments. - Familiarity with security frameworks and compliance standards such as NIST and CMMC. - Familiarity with AI security functionality in enterprise environments including OAuth. - Strong communication skills and the ability to collaborate effectively across technical and non-technical teams. Requirements - Advanced degree or certifications related to AI or machine learning. - Experience integrating AI models into scientific workflows. - Familiarity with large language model (LLM) APIs and orchestration frameworks such as OpenAI, Hugging Face, LangGraph, or LangChain. - Experience with model serving, inference optimization, or AI platform tools such as MLflow, Kubeflow, vLLM, or similar. - Experience with simulations for scientific or engineering projects, particularly physical systems simulations. - Experience with GPU-based systems or running AI models in HPC environments. - Experience writing and deploying MCP Servers on Kubernetes. - DoD experience. - Secret Security Clearance – Active or Inactive. Education - Bachelor’s degree in CS, Software Engineering or other IT-related field or equivalent experience. Benefits - This position may be performed fully remote, hybrid, or onsite at an ARA office. - Preference will be given to candidates located onsite in the Albuquerque, NM and Raleigh, NC area.