• Design, build, and operate AI systems in production with full ownership across reliability, performance, cost, observability, and ongoing model behavior. • Build and maintain data pipelines that ingest, clean, transform, and version the data AI systems depend on, ensuring quality and traceability from source to model. • Design and implement retrieval augmented generation pipelines, vector and graph search systems, and hybrid retrieval strategies that make compliance data accessible for AI driven features. • Fine tune, evaluate, and monitor models against real world performance criteria, with a clear understanding of how to measure what matters in a compliance domain. • Architect and build AI agent systems and orchestration layers that coordinate multi step reasoning, tool use, and decision making across complex GRC workflows. • Build and maintain MCP servers that expose RegScale platform capabilities to AI systems, enabling reliable, secure, and observable AI integrations across the platform. • Design reusable AI primitives and frameworks that product and integration teams can build on, accelerating AI feature development across the organization. • Integrate AI capabilities into CI/CD pipelines with appropriate testing, evaluation gates, and deployment strategies that maintain production quality as models and data evolve. • Partner with Platform Engineering, Core Engineering, and Compliance as Code teams to ensure AI capabilities meet enterprise reliability and security standards. • Proactively identify risks in AI system behavior, data quality, and model performance, bringing proposed mitigations before they become production incidents.

For over four decades, PAR Technology Corporation (NYSE: PAR) has been a leader in restaurant technology, empowering brands worldwide to create lasting connections with their guests. Our innovative solutions and commitment to excellence provide comprehensive software and hardware that enable seamless experiences and drive growth for over 100,000 restaurants in more than 110 countries. Embracing our "Better Together" ethos, we offer Unified Customer Experience solutions, combining point-of-sale, digital ordering, loyalty and back-office software solutions as well as industry-leading hardware and drive-thru offerings. To learn more, visit partech.com or connect with us on LinkedIn, X (formerly Twitter), Facebook, and Instagram. Position Description: We are seeking a pioneering AI Engineer to be the first dedicated AI specialist in the PAR Retail R&D organization. This is a hands-on builder role focused on architecting and integrating our first generation of AI-powered products and services. You will turn business needs into production-ready solutions by leveraging a strong foundation in machine learning alongside modern Generative AI, including agentic workflows that use tools, retrieval, and orchestration to complete real tasks. As our go-to expert, you will define the foundational architecture for integrating modern AI platforms, establish engineering best practices, and drive an experimentation and evaluation mindset to ship reliable solutions. Position Location: - Canada, Remote - United States, Remote Reports To: - Director, Software Development What We’re Looking For: - 5+ years of professional software engineering experience. - 1+ year shipping AI in production, with ideally a progression from applied ML into Generative AI and agentic solutions. - Proven experience building multi-agent systems, orchestrators (planning, task routing, tool calling, state/memory, approvals, retries, and safe fallbacks) and MCP endpoints. - Hands-on experience with agent frameworks and orchestration tooling (e.g., LangGraph, LangChain, LlamaIndex, CrewAI, n8n, or equivalent). - Strong experience with retrieval and grounding: vector databases plus hybrid retrieval/reranking is a plus. - Evaluation-first mindset for agents: test sets, scoring thresholds, regression gates, and quality monitoring over time. - Proven experience architecting solutions using modern AI services from major cloud providers (e.g., Azure OpenAI, Amazon Bedrock, Google Vertex AI). - Strong proficiency in Python and its ecosystem for software development and applied AI. - Experience with Databricks (Delta Lake, Unity Catalog) and deploying AI services (Model Serving); classic MLOps/MLflow is a plus. - Strong ability to “glue” systems together via REST or GraphQL APIs. - Responsible AI experience focused on privacy, security, access control, and defenses against prompt injection and tool misuse. - Excellent problem-solving skills and ability to work independently in a fast-paced, sometimes ambiguous environment. - Bachelor’s degree in computer science or a related technical field. Additional skills: - Experience with advanced approaches beyond LLM apps (e.g., deep learning, classical ML, reinforcement learning) is a plus. - Experience building and operating agentic systems in production: observability (tracing/metrics/logs), CI/CD, and incident-ready monitoring (e.g., DataDog, Grafana). - Experience defining and tracking success metrics for agent workflows (task completion rate, quality scores, latency, cost, escalation rate) plus business KPIs. - Familiarity with full-stack implementation (NodeJS and/or Ruby on Rails) is a plus. - Experience in Fuel and CStore industry, Customer Loyalty, and/or Retail is a strong plus. Unleash your potential: What you will be doing and owning: - Architectural Strategy: Define and establish the foundational architecture and best practices for AI systems across PAR, ensuring solutions are scalable, maintainable, secure, and robust from the ground up. - Zero-to-One Building: Take ambiguous problems from concept to production, building core components and workflows from scratch, iterating quickly through prototypes, and hardening into reliable, repeatable systems. - End-to-End Agentic AI Implementation: Design, build, and operate agentic solutions and workflow automations that go beyond chat, including multi-agent orchestration, MCPs, tool calling, retrieval-grounded reasoning, state/memory, approvals, retries, and safe fallbacks, through production monitoring. - Proof-of-Concept Refinement: Collaborate with other engineers to evaluate existing PoCs. Identify areas for improvement, tighten reliability and quality, and re-architect solutions for scalability, performance, and cost. - Hands-on Technical Contribution: Act as the applied AI subject matter expert within the organization. Provide technical direction to engineers and stakeholders while actively building and shipping. - AI Ops & Infrastructure (LLMOps/AgentOps): Establish and champion production practices for agentic systems, including prompt/version control, evaluation pipelines, tracing/observability, automated testing, release gates, and cost/latency controls. - Strategic Collaboration: Work closely with product managers, data analysts, and business leaders to identify high-impact opportunities for AI. Translate requirements into technical specifications and actionable project plans. - Stay Current: Continuously research and evaluate AI advancements, multi-agent orchestration, and agentic autonomy to keep PAR Retail at the leading edge of practical innovation. Interview Process: - Interview #1: Video Screen with Talent Acquisition Team (via MS Teams) - Interview #2: Video interview with a cross functional partner (via MS Teams) - Interview #3: Video interview with hiring manager (via MS Teams) - Take-home/technical exercise - Interview #4: Technical Interview/Exercise review with a panel (via MS Teams) PAR is proud to provide equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability or genetics. We also provide reasonable accommodations to individuals with disabilities in accordance with applicable laws. If you require reasonable accommodation to complete a job application, pre-employment testing, a job interview or to otherwise participate in the hiring process, or for your role at PAR, please contact accommodations@partech.com. If you’d like more information about your EEO rights as an applicant, please visit the US Department of Labor's website.

We Breathe Life Into Data At Komodo Health, our mission is to reduce the global burden of disease. And we believe that smarter use of data is essential to this mission. That’s why we built the Healthcare Map — the industry’s largest, most complete, precise view of the U.S. healthcare system — by combining de-identified, real-world patient data with innovative algorithms and decades of clinical experience. The Healthcare Map serves as our foundation for a powerful suite of software applications, helping us answer healthcare’s most complex questions for our partners. Across the healthcare ecosystem, we’re helping our clients unlock critical insights to track detailed patient behaviors and treatment patterns, identify gaps in care, address unmet patient needs, and reduce the global burden of disease. As we pursue these goals, it remains essential to us that we stay grounded in our values: be awesome, seek growth, deliver “wow,” and enjoy the ride. At Komodo, you will be joining a team of ambitious, supportive Dragons with diverse backgrounds but a shared passion to deliver on our mission to reduce the burden of disease — and enjoy the journey along the way. The Opportunity at Komodo Health The Analytics Center of Excellence (ACE) team at Komodo Health partners with life sciences organizations to drive strategic value through data, analytics, and AI-enabled solutions. The AI Engagement Manager will play a critical role in ensuring Komodo's AI capabilities are translated into real, measurable impact for our customers. The AI Engagement Manager exists to serve as the primary client-facing point of contact for Komodo's AI-driven initiatives. This role bridges Komodo's internal product, data science, and analytics capabilities with the strategic needs of our clients — working closely with both existing and new customers to integrate Komodo's AI offerings into their workflows, deliver measurable value to key strategic accounts, and drive renewals through sustained client impact. Looking back on your first 12 months at Komodo Health, you will have… - Successfully launched and delivered AI pilots with key strategic accounts, including support for major pharma partnerships. - Established yourself as a trusted advisor to senior client stakeholders across multiple life sciences engagements. - Built strong internal relationships across product, data science, and analytics teams to align delivery with client expectations. - Developed repeatable frameworks and playbooks for AI engagement scoping and delivery that the broader ACE team can leverage. - Contributed to account growth by identifying expansion opportunities within existing client relationships. You will accomplish these outcomes through the following responsibilities… - Own a significant portion of direct project delivery for client engagements, with support from team members as needed. - Serve as the primary point of contact for clients throughout the AI engagement lifecycle, from initial scoping and pilot design through execution and final delivery. - Lead strategic advisory conversations with senior client stakeholders, translating Komodo's AI capabilities into actionable solutions for their business needs. - Manage 3-5 concurrent AI engagements, balancing timelines, deliverables, and client expectations across accounts. - Support presales and renewal conversations by bringing credible AI and life sciences expertise to the table. - Proactively identify risks and opportunities within client engagements, escalating or acting as appropriate. - Contribute to the development of the AI engagement practice by documenting learnings and refining delivery processes over time. What you bring to Komodo Health (required): - Willingness to travel approximately 50% of the time to support client engagements. - Experience in management consulting with a focus on strategic advisory work, preferably at a top-tier or life sciences-focused firm. - Direct experience working with pharmaceutical, biotech, or broader life sciences clients. - Hands-on experience scoping, managing, or delivering AI or digital transformation pilots in a client-facing context. - Strong executive presence with the ability to lead complex conversations with senior stakeholders. - Excellent project management skills — comfortable managing multiple engagements simultaneously in a fast-moving environment. - Familiarity with healthcare data, commercial life sciences functions, or real-world evidence. - Ability to operate with autonomy and adapt quickly in a high-growth, ambiguous environment. Expectations of AI Use in this role (required): Judgement & Creativity: - Applies AI strategically, knowing how to use the right tools at the right time to solve problems or generate new ideas. - Uses AI to accelerate feedback loops, test ideas, and make informed decisions faster. - Applies both judgment and creativity when working with AI and understands its limitations. Curiosity & Initiative: - Demonstrates curiosity and initiative in exploring new AI tools and workflows relevant to their role. - Has developed or shared AI-enhanced workflows, automations, or prompts with others. Integration & Productivity: - Brings a reflexive AI mindset and uses AI as a natural part of their process to iterate, research, and deliver better work. - Comfortable working in AI-enhanced environments across writing, data analysis, content creation, or design. - Regularly leverages AI tools such as Notion AI, Perplexity, Claude, Descript, Runway, Midjourney, or Microsoft Copilot i.e. to improve speed, clarity, or creative output. #LI-Remote The pay range for each job posting reflects a minimum and maximum range of annual base pay that we reasonably expect to pay for this position within the US. We carefully consider multiple business-related factors when determining compensation, including job-related skills, work experience, geographic work location, relevant training and certifications, business needs and market demands. The starting annual base pay for this role is listed below. This position may be eligible for performance-based bonuses as determined in the Company’s sole discretion and in accordance with a written agreement or plan. This role may also be eligible for equity awards. In addition, this role is eligible for benefits including, but not limited to, comprehensive health, dental, and vision insurance; flexible time off and holidays; 401(k) with company match; disability insurance and life insurance; and leaves of absence in accordance with applicable state and local laws and regulations and company policy. San Francisco Bay Area and New York City: $163,000—$220,000 USD All Other US Locations: $142,000—$190,000 USD Komodo's AI Standard At Komodo, we're not just witnessing the AI revolution – we're leading it. This is a pivotal moment in time, where being first to market with AI transforms industries and sets the bar. We've already established industry leadership in leveraging AI to revolutionize healthcare, and we expect every team member to contribute. AI here isn't optional; it's foundational. We expect you to integrate AI into your daily work – from summarizing documents to automating workflows and uncovering insights. This isn't just about efficiency; it's about making every moment more meaningful, building on trust in AI, and driving our collective success. Join us in shaping the future of healthcare intelligence. Where You’ll Work Komodo Health has a hybrid work model with hubs in San Francisco, New York City, and Chicago. Roles vary — some can be performed from anywhere in the country, others are scoped to a specific region, and some are based near one of our hubs. For hub-based Dragons, we're building intentional in-office rhythms alongside the flexibility that's core to how we work. Whatever your setup, expectations will always be clear before you join. Equal Opportunity Statement Komodo Health provides equal employment opportunities to all applicants and employees. We prohibit discrimination and harassment of any type with regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. By submitting your application, you acknowledge that you have read and understand Komodo Health’s Privacy Notice for Employees and Contractors. This notice explains how we collect, use, and retain applicant data.

Role Description We are looking for a talented AI Research Engineer to join our computer vision research team. In this role, you will work closely with our research team, implementing, training, and evaluating state-of-the-art image and video generation models. You will own the engineering execution that turns research ideas into working systems: - Building robust data pipelines - Running and stabilizing large-scale training - Implementing models from papers - Optimizing for speed/efficiency - Running rigorous evaluations This is a high-impact implementation and execution role. This role is ideal for engineers who enjoy building reliable ML systems and scaling research ideas into production-quality training pipelines. The ideal candidate is someone who gets deep satisfaction from: - Making complex systems work - Translating research ideas into reliable, scalable code - Debugging training instabilities - Delivering measurable improvements in training stability, model quality, and inference efficiency This is an excellent opportunity to work closely with experienced researchers, gain deep hands-on exposure to cutting-edge model training techniques, latest research methods in diffusion/transformer-based generation, large-scale experimentation, and efficiency innovations, all while contributing directly to production-grade models. Qualifications - 2–5 years of hands-on experience building and training ML systems, with strong ownership of results - Fluency in PyTorch: comfortable reading, writing, and debugging both training and inference code - Experience training or fine-tuning generative models (diffusion models, transformers, VAEs, or similar) from scratch or near-scratch - Solid understanding of distributed training workflows and practical debugging of large training runs - Demonstrated ability to read and implement AI research papers in computer vision - Familiarity with cutting-edge computer vision models and research literature in the image and video domain - Experience building data pipelines for large-scale image or video datasets - Strong debugging skills: comfortable diagnosing both engineering bugs and training failures - Strong engineering mindset: writing clean, reliable, debuggable code; profiling tools; handling numerical issues at scale Requirements - Build and maintain end-to-end data pipelines for large-scale image and video datasets: collection, filtering, augmentation, conditioning alignment, and efficient storage/sampling - Implement model architectures (diffusion, autoregressive, flow-based, diffusion transformers, etc.) and maintain high-throughput PyTorch training loops for large-scale image and video diffusion models - Run and manage large-scale training experiments on multi-GPU and multi-node setups (DDP, FSDP, DeepSpeed) - Debug training instabilities, loss spikes, and convergence issues - Apply quantization, pruning, and knowledge distillation techniques to compress models without sacrificing quality - Collaborate with researchers and translate state-of-the-art research papers into working implementations in our internal codebase (e.g., new attention mechanisms, sampling schedules, or conditioning methods) - Build and maintain evaluation pipelines of image quality, video consistency, and perceptual metrics - Set up and maintain human annotation and evaluation pipelines using services like AWS GroundTruth - Profile and optimize training speed, GPU memory utilization, and iteration time - Implement inference optimizations to reduce latency and compute cost - Work with acceleration toolchains such as torch.compile, Triton, TensorRT, or ONNX where appropriate Benefits - Competitive salary and generous company equity - Medical, dental, and vision insurance – 99.99% of premiums covered by Cantina - 42 days of paid time off, including: - 15 PTO days - 10 sick days - 15 company holidays - 2 floating holidays - Generous parental leave & fertility support - 401(k) retirement savings plan - Lifestyle spending account – $500/month to use however you’d like - Complimentary lunch and snacks for in-office employees - One Medical membership, and more!