Impact Advisors, LLC is a nationally recognized healthcare management consulting firm delivering Best in KLAS advisory, implementation, and optimization services. We are driven by a commitment to exceed client expectations and are proud to be a trusted partner to many of the nation's leading healthcare organizations. Our mission to drive patient-centered, value-driven outcomes has earned us prestigious industry accolades. To learn more about us, visit www.impact-advisors.com Job Overview Impact Advisors is seeking an experienced and results-oriented AR Manager to lead accounts receivable operations across our healthcare client engagements. In this role, you will oversee revenue cycle performance, drive operational excellence, and manage high-performing teams focused on billing, follow-up, and collections. As an AR Manager, you will serve as both an operational leader and trusted advisor to clients. You will be responsible for inspiring and developing teams, proactively identifying performance gaps, and implementing practical, sustainable solutions. This role requires a hands-on leader who is willing to roll up their sleeves when needed while also maintaining executive-level visibility and strategic oversight. You will partner directly with client leadership to improve cash flow, reduce denials, and strengthen overall revenue cycle. Success in this role requires the ability to quickly gain client confidence, secure buy-in for change initiatives, and identify opportunities to expand Impact Advisors’ footprint through strong delivery and relationship management. This is an opportunity to join a growth-oriented, private equity-backed firm where you can influence client outcomes, lead operational transformation, and make a meaningful impact on healthcare financial performance. Responsibilities • Lead day-to-day AR operations, including billing, follow-up, denial management, and collections for assigned healthcare clients. • Inspire, mentor, and develop AR teams, fostering a culture of accountability, engagement, and high performance. Mange underperformance through correct action plan. • Establish productivity and quality standards; monitor key performance indicators such as days in AR, aging, denial rates, and cash collections. • Proactively identify operational issues, root causes of underperformance, and implement timely corrective action plans. • Contribute to development and maintenance of SOPs and job aids, in correlation with internal teams and client teams. Ensure adoption and adherence for AR rep team of SOPs and job aids. • Apply a hands on approach as needed to support complex accounts, escalations, and high-priority client initiatives. • Prepare and deliver executive-level weekly and monthly performance reports highlighting trends, risks, and improvement opportunities. • Analyze payer behavior and claims data to identify systemic denial patterns and drive resolution strategies. • Coordinate resolution of claim edits, claim definition files, billing rules, and system-related issues. • Oversee account assignments to ensure timely processing, triage, and resolution of outstanding balances. • Build strong, trusted relationships with client stakeholders, gaining confidence and buy-in for operational improvements. • Partner with client and internal leadership to drive continuous process improvement and identify opportunities to expand services and deepen engagement. • Facilitate communication with payers to address escalated claims and systemic reimbursement issues. Qualifications Education and Experience • Associate’s degree in Business, Healthcare Administration, or related field required; Bachelor’s degree preferred. • 3+ years of healthcare revenue cycle experience (billing and collections required). • Minimum 1 year of leadership or supervisory experience required; 3+ years of revenue cycle management experience preferred. • Experience within large, complex healthcare systems (academic medical center experience preferred). • Epic experience required; Epic certification(s) required or ability to obtain. • Authorized to work in the United States. Skills and Competencies • Strong understanding of accounts receivable management, denial prevention, payer trends, and revenue cycle KPIs. • Proven ability to motivate and inspire teams while maintaining high standards of accountability. • Strong problem-solving skills with the ability to quickly diagnose issues and implement effective solutions. • Client-facing presence with demonstrated ability to build trust, influence stakeholders, and drive adoption of change. • Entrepreneurial mindset with the ability to identify growth opportunities within existing engagements. • Strong analytical skills with proficiency in Microsoft Excel and PowerPoint. • Excellent written and verbal communication skills with the ability to present to executive stakeholders. Additional Information - Travel: 40-60% nationwide travel At Impact Advisors, we are committed to transparency and equity in our compensation practices. The compensation for this role includes an annual salary range of $125,000 to $200,000 For salaried positions, this role may also be eligible for an annual performance bonus. Additional benefits and perks may also be available, depending on the position and employment terms. This range reflects consideration of several factors, including skills, experience, training, certifications, and organizational needs. For salaried positions, this role may also be eligible for an annual performance bonus. Additional benefits and perks may also be available, depending on the position and employment terms. This range reflects consideration of several factors, including skills, experience, training, certifications, and organizational needs. Our People and Culture At Impact Advisors, we cultivate a caring, fun, honest, and autonomous work environment. Our success stems from our associates' dedication and a shared mission to create a “Positive Impact.” We embrace diversity and inclusion, fostering an environment where all employees feel valued and empowered. Join Impact Advisors and make a real difference in healthcare.

Build the Future of AI-Driven Digital Platforms Arena is building a new generation of AI-first digital entertainment platforms. Since 2021 we’ve launched multiple brands including MetaWin, WOW Vegas, BetZoo Media, Hit.com and Rolla, with more in development. Our platforms combine high-scale systems, immersive user experiences, and modern AI infrastructure. We operate globally with teams across London, Gibraltar & Miami Unlike many companies, we aren’t constrained by legacy systems. We design and build AI-first platforms from the ground up, using modern infrastructure, distributed systems, and emerging AI tooling to move faster and build better products. We’re looking for engineers who want to build real systems, deploy AI in production, and ship fast. The Role We’re enhancing our core development team with new opportunities for Applied AI Engineers / Forward Deployed Engineers. This team will work directly on the frontline of engineering and AI deployment, embedding AI capabilities into the core of our platforms. This is not a research role and not a corporate engineering job. You will: - Design systems - Build prototypes - Deploy AI into production - Work directly with product and engineering teams - Ship software at high velocity You will help define how AI is / could be used across our portfolio of products. What You'll Work On - Building AI-powered product features - Developing LLM-powered systems and internal tooling - Deploying AI agents, workflows, and automation - Integrating multiple model providers and AI infrastructure - Building backend services that support AI-driven applications - Rapid prototyping and shipping new ideas into production - Improving developer productivity with AI-native engineering workflows We value engineers who are comfortable moving from concept → prototype → production quickly. AI Tooling We’re Exploring We actively experiment with modern AI engineering ecosystems, including: AI Engineering Tools - Claude Code - Codex - OpenRouter - OpenCode - OpenClaw Models - Kimi - Qwen - Frontier and open-source LLMs Experience with multi-model orchestration and applied AI systems is particularly valuable. What We’re Looking For You are likely someone who: - Has a strong software engineering foundation - Builds things outside of work - Has already experimented with LLM tooling or AI developer workflows - Is comfortable working across backend systems and APIs - Likes moving fast and shipping real software - Is excited about the practical application of AI in production systems We care far more about what you’ve built than where you’ve worked. This Role Is Probably NOT For You If - You prefer slow-moving corporate environments - You want highly structured roles and rigid process - You are primarily interested in AI research rather than shipping products Why Arena - AI-first engineering culture - Build products used by millions of users - Work with a small, highly capable team - Freedom to experiment with new AI tooling and models - Opportunity to shape how AI is deployed across a global product ecosystem If you're an engineer who enjoys building quickly, experimenting with AI, and shipping real systems we want to hear from you.

• Advanced Prompt Engineering: Designing complex, dynamic prompt templates with conditional logic and efficiently reusing information and context within prompts to maximize generation quality and reasoning. • Structured Outputs & Schemas: Implementing various response schemes (JSON mode, function calling, Zod/JSON schemas) to ensure AI outputs are predictable and ready for seamless integration into application logic. • Prompt Engineering & Evaluations: Building robust evaluation pipelines and using Langfuse to collect feedback and score the quality of responses in real time. • Tracing & Debugging: Performing deep debugging of complex LLM chains using Langfuse traces to identify bottlenecks and optimize for cost, latency, and context window usage. • AI A/B Testing: Running systematic experiments across different models via OpenRouter (e.g., comparing Claude 3.5 Sonnet vs. GPT-4o) and analyzing results based on quantitative metrics. • Data-Driven Decisions: Making deployment decisions for new prompts or models strictly based on quantitative benchmarks and trace data, rather than intuition. • Output Scoring & Analysis: Developing scoring systems to analyze the “Problem → Solution” chain and identify root causes of hallucinations or logic errors using Langfuse analytics. • Model Performance & Fine-Tuning: Regularly re-evaluating model performance as new architectures emerge and performing fine-tuning when necessary to meet specific domain requirements.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description This role involves owning the end-to-end machine learning lifecycle for production AI systems. - Own the full ML lifecycle, including data ingestion, training, validation, deployment, monitoring, retraining, and retirement. - Transition AI/ML prototypes into scalable, production-ready systems with CI/CD pipelines, automation, and observability. - Lead system design and architecture discussions, providing guidance on ML systems, MLOps, and AI infrastructure. - Develop and maintain AI-driven applications and inference services, optimizing for performance, scalability, reliability, and cost. - Integrate LLMs, generative AI, and NLP solutions into IMO Health products, focusing on unstructured clinical data. - Implement monitoring, alerting, logging, and dashboards to ensure model quality, detect drift, and maintain operational SLAs. - Build, maintain, and optimize CI/CD pipelines, automation scripts, and Infrastructure-as-Code for production ML systems. - Apply containerization (Docker, Kubernetes) and cloud infrastructure best practices to manage production environments. - Mentor and guide engineers, enforce technical standards, and drive reduction of technical debt. - Conduct root cause analysis of production defects and implement durable fixes. - Advocate for non-functional requirements (availability, scalability, reliability, maintainability) and design systems accordingly. - Collaborate cross-functionally with Product, Data Science, Architecture, and Engineering teams to align AI solutions with business goals. Qualifications - 8+ years of professional experience in software engineering, AI/ML engineering, or related roles, building and operating production-grade systems. - Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field (or equivalent experience). - Strong foundation in computer science fundamentals (data structures, algorithms, design patterns, operating systems, networking). - Expert-level coding skills in Python or Java, with a strong emphasis on production-quality software engineering practices. - Hands-on experience owning ML systems in production, including deployment, monitoring, retraining, and optimization. - Experience designing and operating CI/CD pipelines, automation, and observability for ML systems. - Deep experience with cloud platforms (AWS or Azure), containerization, and Infrastructure-as-Code. - Experience with MLOps tools and workflows (e.g., MLflow, SageMaker, Kubeflow). - Experience integrating and deploying LLMs, generative AI, and agentic systems in production environments. - Working knowledge of NLP concepts (tokenization, embeddings, classification, sequence modeling); healthcare exposure is a plus. - Experience with Elasticsearch and vector databases for embedding-based search and retrieval. - Proven ability to translate business needs into scalable, reliable technical solutions, balancing technical debt and delivery velocity. - Strong system design skills for high-performance, distributed, and scalable systems. - Excellent communication and collaboration skills across cross-functional, distributed teams. - Self-starter who can operate autonomously and own complex systems end to end. Requirements - Experience with clinical or healthcare AI applications. - Familiarity with Hugging Face, PyTorch, TensorFlow, or other modern ML frameworks. - AWS Associate-level certification (Machine Learning Engineer or Solutions Architect). Benefits - Compensation range: $170,000 - $250,000 a year. - Comprehensive benefits package.