Role Description This role offers a high-impact opportunity to design, develop, and maintain Apple applications that reach millions of users worldwide. You will play a key role in shaping the architecture, performance, and security of iOS, macOS, tvOS, and watchOS applications while collaborating with cross-functional teams across product, design, and backend development. You will contribute to a culture of high-quality code, test-driven development, and modern engineering best practices. This position emphasizes innovation, mentorship, and technical leadership, empowering you to make decisions that directly enhance user experience, app reliability, and scalability in a fast-moving, security-focused environment. Accountabilities: - Define and implement the architecture of Apple applications across iOS, macOS, tvOS, and watchOS platforms. - Collaborate closely with product managers, designers, and backend engineers to build new features and enhance existing functionality. - Develop secure networking and connectivity layers, including VPN-related functionality, to maintain privacy and performance standards. - Translate UI/UX designs into responsive, visually appealing, and user-friendly interfaces. - Write clean, modular, maintainable, and well-documented code following OOP principles and modern Swift best practices. - Implement unit tests and contribute to a test-driven development (TDD) culture to ensure code reliability. - Participate in code reviews to uphold coding standards, performance, and security practices. - Continuously optimize app performance, network reliability, and stability. - Mentor and support junior engineers, sharing knowledge and fostering a collaborative team environment. Qualifications - Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field preferred. - Extensive experience developing Apple applications using Swift, SwiftUI, UIKit, and Combine. - Strong knowledge of Swift Concurrency (async/await, Task, structured concurrency) and asynchronous programming patterns. - Familiarity with networking protocols (TCP/IP, HTTPS, TLS, DNS) and connection management. - Experience with VPN technologies, secure networking, or Apple Network Extension frameworks is highly valued. - Proficiency integrating RESTful APIs, JSON, and web services. - Solid understanding of software development lifecycle (SDLC) processes, version control (Git), CI/CD, and code review practices. - Demonstrated ability to write well-structured, modular, maintainable code with attention to performance and scalability. - Experience with unit testing, test-driven development, and automated testing tools. - Strong problem-solving, debugging, and analytical skills. - Ability to mentor and collaborate with team members, fostering a culture of learning and innovation. - Passion for staying up-to-date with emerging trends, frameworks, and best practices in Apple development. Benefits - Competitive salary based on experience and qualifications. - Flexible work environment supporting remote collaboration. - Career growth opportunities and mentorship programs. - Focus on learning and experimentation in a supportive, innovative culture. - Health and wellness support through employee programs and initiatives. - Collaborative team environment where engineers have autonomy and ownership over technical decisions. - Exposure to cutting-edge Apple technologies and security-focused app development.

Role Description This role leads a high-impact AI inference engineering team, driving the design, deployment, and optimization of large-scale AI model serving systems. You will bridge research and production, architecting high-throughput, low-latency inference pipelines while mentoring a tight-knit team of developers. The position combines hands-on technical work with strategic leadership, influencing the evolution of cutting-edge AI infrastructure. You will evaluate emerging inference frameworks, optimize GPU utilization, and deliver scalable solutions for demanding AI workloads. This is an ideal opportunity for professionals passionate about pushing the boundaries of AI infrastructure and shaping a high-growth engineering organization. - Architect, deploy, and optimize AI inference pipelines for large-scale language models, ensuring high throughput, low latency, and efficient GPU utilization. - Lead and mentor a small team of engineers, providing guidance through code reviews, sprint planning, and career development. - Implement and evaluate advanced KV cache management strategies and speculative decoding approaches to minimize redundant computation. - Integrate and optimize serving engines and frameworks to maximize hardware efficiency and system performance. - Conduct research and benchmarking of new tools and frameworks, maintaining expertise in the evolving AI inference landscape. - Collaborate with cross-functional teams to translate research innovations into production-grade systems. - Drive continuous improvement in infrastructure, scalability, and operational best practices for AI workloads. Qualifications - 8+ years of experience in backend or infrastructure engineering, with a focus on AI inference, GPU optimization, or distributed systems. - Proven hands-on expertise in AI model serving, including LLM deployment and inference pipeline optimization. - Deep experience with inference frameworks such as vLLM, LMCache, LLM-d, and NIXL. - Strong programming skills in Python, C++, or Rust, with practical knowledge of CUDA and GPU memory management. - Experience with Kubernetes for scaling AI workloads and optimizing startup times. - Familiarity with KV cache reuse, speculative decoding, and batching strategies for inference efficiency. - Excellent leadership, communication, and mentoring skills, with experience guiding small engineering teams. - Ability to balance hands-on engineering with strategic architectural decisions in a fast-paced, high-growth environment. Benefits - Competitive base salary with total compensation determined based on experience, location, and qualifications. - Equity opportunities in a high-growth, pre-IPO company. - Comprehensive health benefits including medical, dental, vision, and life insurance. - 401(k) retirement plan with employer match. - Flexible time off, sick leave, and parental leave programs. - Opportunities to work on cutting-edge AI infrastructure projects and shape a growing engineering team.

Job Description Position: Senior Forward Deployed Engineer Reports To: SVP, Private Deployments Location: Remote (US) Job Overview We are seeking a highly capable and results-driven professional to join our team in the role of Senior Forward Deployed Engineer to join our Reveal Private Deployment (RPD) team. This position plays a key role in supporting the organization's goals by contributing to bridge Reveal’s cloud-native engineering capabilities with customer-hosted environments and requires a customer-first mindset. The successful candidate is a blend of customer-facing engineer, technical expert, and natural problem solver. You will lead implementations, provide expert technical recommendations, and identify opportunities for continuous improvement in both customer environments and internal deployment processes. You bring strong Kubernetes, Helm, and infrastructure-as-code expertise, along with the ability to engage directly with enterprise customers during all phases. When you’re not leading customer implementations, you’ll focus on optimizing deployments for simplicity, developing standards for deployment, and providing expert assistance to existing customers who need additional technical assistance. While this role is primarily remote, you’ll still enjoy strong connectivity with your team and clients. You’ll have access to a collaborative network of colleagues who are committed to timely and effective client support. Our team culture emphasizes communication, responsiveness, and shared success—no matter where you're working from. We provide the tools and support needed to thrive in a virtual environment, ensuring you feel connected and empowered every step of the way. Responsibilities & Duties - Partner with customers to provide technical architecture guidance, sizing recommendations, and deployment strategy. - Lead in deployments and configurations of Reveal Private Deployment environments. - Work directly with Reveal infrastructure and development teams to ensure alignment between SaaS and on-premise architectures. - Contribute to and maintain Helm charts, Terraform modules, and other infrastructure-as-code resources used for deployment automation. - Support and troubleshoot complex Kubernetes environments, including networking, storage, and security integrations. - Provide Tier-3 technical escalation and root-cause analysis for customer deployments. - Develop and maintain detailed documentation, operational runbooks, and best-practice guidance. - Share learnings and feedback from customer engagements to improve Reveal’s products and processes. Characteristics - Customer-first mindset with a strong sense of ownership and accountability for client success. - Exceptional problem-solving ability; able to break down complex technical issues into clear, actionable solutions that balance customer needs and engineering constraints. - Excellent written and verbal communication skills with both technical and non-technical audiences. - Collaborative and proactive, comfortable working across infrastructure, development, and customer success teams. - Resourceful, analytical, and persistent in diagnosing complex technical challenges. - Motivated to improve automation, repeatability, and deployment quality for customer-facing solutions. Education & Experience - 8+ years of experience in DevOps, infrastructure engineering, or software deployment roles. - Deep hands-on experience with Kubernetes, including AWS, Azure, and bare-metal clusters. - Strong experience authoring and maintaining Helm charts and infrastructure-as-code (Terraform, Ansible, or similar). - Experience with CI/CD tools such as GitHub Actions. - Proficiency in Windows and Linux administration, scripting (Python/Bash), and CI/CD pipelines. - Knowledge of container networking, storage, and security fundamentals. - A bachelors degree or equivalent work direct work experience. - Willingness to travel up to 25% for customer engagements. Preferred Experience - Experience in eDiscovery environments is a plus, not required. - Experience with administration and high availability for Microsoft SQL Server and Postgres Benefits and Perks including but not limited to: - 401k match program - Comprehensive health benefits (Medical, Dental, Vision, and HSA/FSA) - Group Term Life Insurance and Voluntary Life Insurance option - Paid holidays - Paid vacation, sick, and personal days - FSA dependent care benefit - Childbirth recovery and bonding leave policies - Short and long-term disability benefits For Illinois-based roles, the budgeted annual salary range is $170,000 to $180,000. Compensation for this role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience, and may fall outside of the range shown. Reveal offers a competitive total rewards package, which includes the Benefits and Perks set forth above. This job description reflects the present requirements of the position. As duties and responsibilities change and develop, the job description will be reviewed and subject to amendment. Hiring Policy Reveal is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. Reveal does not discriminate in employment on the basis of race, color, religion, sex (including pregnancy and gender identity), national origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non-merit factor. Reveal considers candidates with existing visas but does not sponsor new visa applications.

• Design, develop, and deploy AI/ML models for enterprise-grade applications. • Build end-to-end ML pipelines including training, evaluation, optimization, deployment, and monitoring. • Architect and develop agentic AI systems including multi-agent workflows, RAG chatbots, and intelligent automation. • Build RAG (Retrieval-Augmented Generation) applications tailored to insurance workflows. • Develop multi-agent orchestration systems for complex P&C processes. • Drive company-wide AI adoption by identifying high-impact use cases across P&C insurance functions. • Conduct experimentation and research with state-of-the-art AI techniques and frameworks. • Establish AI development standards, best practices, and governance frameworks. • Collaborate with our Python-strong data engineering team on backend integrations.