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 overseeing the full software development lifecycle for solutions built on Java, Spring Boot, and Kafka, managing complex, scalable projects from inception to production. - Lead an engineering team in the design, development, coding, testing, deployment, and debugging of distributed applications and microservices - Collaborate directly with product owners to understand business requirements, develop strategies, and create technical roadmaps aligned with business objectives - Work closely with other lead engineers and stakeholders to design robust technical solutions and approaches for new product features - Instill best practices for software development, code quality, documentation, and delivery of high-quality work within tight timelines - Manage project prioritization, feature planning, stakeholder communication, and tracking of external commitments - Translate business requirements into effective technical solutions; recommend alternative approaches to meet aggressive deadlines with optimal results - Champion operational excellence, including building, deploying, monitoring, and supporting production services, with a focus on reliability and scalability - Guide and mentor junior developers, fostering career growth and technical skill development within your team - Drive the adoption of AI productivity tools and modern development practices to improve engineering efficiency - Lead incident response efforts; troubleshoot and resolve production issues efficiently, including participation in war rooms when required - Promote quality through Test-Driven Development (TDD), Agile methodologies, and continuous improvement initiatives Qualifications - Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field - 6+ years of hands-on experience in software engineering, with deep expertise in Java, Spring Boot, and event-driven architectures using Kafka - Proven experience leading engineering teams, including mentoring, technical guidance, and team development - Experience with relational databases and data modeling - Experience with cloud-native development (AWS, Azure, or GCP), containerization (Docker), and orchestration (Kubernetes) - Experience working within Agile development teams - Experience with event streaming, high-throughput data processing, and real-time systems - Experience managing and resolving production incidents, including root cause analysis and postmortem documentation - Solid understanding of CI/CD pipelines, test automation, and modern DevOps practices - Familiarity with design and architectural patterns including Domain-Driven Design - Familiarity with using AI-powered tools to enhance productivity and streamline development processes - Proven solid background in designing, developing, and deploying secured RESTful APIs - Demonstrated ability to prioritize work, manage multiple projects, and communicate effectively with product teams and other engineering leads - Proven excellent interpersonal and communication skills, with a collaborative mindset Preferred Qualifications - Proven solid problem-solving and analytical skills, with the ability to think critically and propose innovative technical solutions - Proven excellent communication and collaboration skills, with the ability to work effectively with both technical and non-technical stakeholders - Demonstrated passion for continuous learning and staying up to date with the latest advancements in cloud technologies and AI/ML Requirements - All employees working remotely will be required to adhere to UnitedHealth Group’s Telecommuter Policy Benefits - Comprehensive benefits package - Incentive and recognition programs - Equity stock purchase - 401k contribution (all benefits are subject to eligibility requirements) Application Deadline This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants.

• Own feature development: Take ownership of features end-to-end — from technical design through delivery — breaking complex UI and interaction flows into well-scoped, deliverable pieces. • Write high-quality code: Produce TypeScript and React Native code that is clean, performant, well-tested, and raises the bar for the codebase. • Contribute to architecture: Participate in team-level architectural decisions around component patterns, state management, navigation, and performance optimization. • Improve quality proactively: Identify opportunities to improve app performance, code quality, accessibility, and developer experience — and act on them. • Guide junior engineers: Provide technical guidance to Software Engineers I and II through thorough code reviews, pairing sessions, and design feedback. • Collaborate cross-functionally: Work with Product, Design, and QA to validate technical decisions and ensure alignment between product goals and implementation. • Participate in on-call rotation: Take increasing ownership of incident response, contributing to root cause analysis and systemic improvements. • Build team knowledge: Document technical decisions, component patterns, and architecture to strengthen your team’s shared understanding.

• Utilize advanced analytical tools, including Production Cost Models (“PCM”s) such as GridView, to assist with generation, storage and transmission capacity investment decisions. • Simulate the detailed operation of power systems on an hourly to sub-hourly basis using PCM. • Assess resource adequacy and reliability, analyze the impacts of capacity changes on system operations, evaluate transmission congestion and locational marginal prices, and provide comprehensive analyses of daily emission patterns. • Develop and validate hypotheses regarding the economics of power system operations. • Focus on maximizing societal net benefits through effective supply-and-demand balance and minimizing total system costs associated with infrastructure and new resource investments. • Strategically create and implement all necessary PCM study scenarios, supporting various reasonable hypotheses, and prepare detailed study reports that showcase major findings. • Execute additional power system studies as needed, contributing your expertise to enhance power system understanding and reliability.

Location: Remote US Start date: ASAP Languages: English (required) About the Role Pragmatike is hiring on behalf of a fast-growing AI startup recognized as a Top 10 GenAI company by GTM Capital, founded by MIT CSAIL researchers. We are searching for a CUDA Kernel Engineer who has hands-on experience developing and optimizing NVIDIA CUDA kernels from scratch. You will work on the GPU performance layer powering large-scale, high-throughput AI systems used by Fortune 500 customers. This role is ideal for someone who deeply understands NVIDIA GPU architecture, memory hierarchy, warp-level execution, and profiling workflowsnot someone coming from generic hardware, FPGA, or non-NVIDIA compute backgrounds. You will directly influence the GPU efficiency, throughput, and scalability of mission-critical AI systems. What Youll Do - Design, implement, and optimize custom CUDA kernels for NVIDIA GPUs, with a focus on maximizing occupancy, memory throughput, and warp efficiency. - Profile GPU workloads using tools such as Nsight Compute, Nsight Systems, nvprof, and CUDA‐MEMCHECK. - Analyze and eliminate performance bottlenecks including warp divergence, uncoalesced memory access, register pressure, and PCIe transfer overhead. - Improve GPU memory pipelines (global, shared, L2, texture memory) and ensure proper memory coalescing. - Collaborate closely with AI systems, model acceleration, and backend distributed systems teams. - Contribute to GPU architecture decisions, kernel libraries, and internal performance-engineering best practices. What Were Looking For - Proven track record building NVIDIA CUDA kernels from scratchnot just calling existing libraries. - Strong ability to optimize kernels (tiling strategies, occupancy tuning, shared memory design, warp scheduling). - Deep understanding of CUDA threads, warps, blocks, and grids, GPU memory hierarchy and memory coalescing, as well as warp divergence (how to detect, analyze, and mitigate it) - Experience diagnosing PCIe bottlenecks and optimizing host-device transfers (pinned memory, streams, batching, overlap). - Familiarity with C++, CUDA runtime APIs, and GPU debugging/profiling tooling. Bonus Points - Experience with multi-GPU or distributed GPU systems (NCCL, NVLink, MIG). - Background in GPU acceleration for ML frameworks or HPC workloads. - Knowledge of model inference optimization (TensorRT, CUDA Graphs, CUTLASS). - Exposure to compiler-level optimization or PTX/SASS analysis. - Startup experience or comfort working in fast-moving, ambiguous environments. Why This Role Will Pivot Your Career - Research pedigree: MIT CSAIL founders recognized for breakthrough AI and systems contributions. - Customer impact: Deploy AI solutions powering Fortune 500 clients. - Industry momentum: Lab alumni have led high-value acquisitions (MosaicML Databricks, Run:AI Nvidia, W&B CoreWeave). - Funding & growth: Oversubscribed seed round, next funding in 2026. - Career growth & influence: Lead AI initiatives, optimize pipelines, and directly impact production AI systems at scale. - Culture & autonomy: Own critical systems while collaborating with world-class engineers. - Aspirational impact: Solve GPU/AI performance challenges few engineers ever face. Benefits - Competitive salary & equity options - Sign-on bonus - Health, Dental, and Vision - 401k Pragmatike is an Equal Opportunity Employer and is committed to providing equal employment opportunities to all applicants without discrimination. We recruit on behalf of our clients and prohibit discrimination and harassment based on 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. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.We are committed to a fair and inclusive hiring process. We process your personal data solely for recruitment purposes, in accordance with applicable privacy laws, and maintain reasonable safeguards to protect your information. Your data may be shared with our client(s) for hiring consideration, but will not be disclosed to third parties outside of the recruitment process.