AryaXAI offers one of the most reliable, safe, and performant platforms for building Expert AI Agents & Models for mission-critical use cases. We stand at the forefront of AI innovation, revolutionizing AI for mission-critical businesses by solving the most critical challenges in AI interpretability, alignment, and AI risk. Through our research labs in Mumbai, Paris, and London, we produce state-of-the-art techniques, models, and open-source tools. The platform integrates these components and scales them to the users and usage as needed. We are ardent supporters of OSS, and we not only open-source our research but also integrate multiple OSS to deliver the scale. At AryaXAI, everyone contributes hands-on to our mission in a flat organizational structure that values curiosity, initiative, and exceptional performance. Qualifications We are now looking for highly experienced Senior Engineering Managers who can lead the platform scale and components, and make it the industry best in the relevant components. Ideal candidates should have at least 5+ years of experience working with products that require heavy engineering and scaling requirements. Preference is from a product background with strong discipline around the stack and PR quality. 5+ years of experience in building and deploying enterprise-grade machine learning infra, SaaS software, data analytics solutions, or online platforms 2+ years of experience in building LLM infra or high-volume AI inference components. Academic degree in Computer Science, Engineering, or a related field Strong background in Python programming, Distributed computing, Engineering, big data processing, and cloud computing (AWS, Azure, GCP, on-premises) Experience in optimizing, scaling, and reliability of large-scale systems for various data modalities and AI models. Strong fundamentals and discipline in CI/CD pipelines, containerization (Docker, Kubernetes), and multi-cloud environments. Proven track record in product management in designing and delivering complex, high-performance solutions for large-scale enterprise customers without faults and the ability to auto-scale the systems through delivering the essential SLAs in production during inference Programming skills - expert in Python and solid coding practices Data Engineering - expert in MongoDB and strong fundamentals in data lakes, data storage, ETL pipelines, and building real-time data pipelines. Strong material skills, excellent communication, collaboration, and leadership skills with the ability to lead teams, mentor juniors, and work with other teams. Strong system architecture background that supports scaling in regulated industries. Experience in scaling AI/ML production systems using classic ML models, LLMs, and Deep Learning models on traditional hardware and high-performance computing. Roles And Responsibilities As Sr Engineering Manager, you'll be the main SPOC for all the engineering efforts behind the AryaXAI platform, serving customers in SaaS and on-premise modes and scaling multiple AI models in startups, SMEs, and highly regulated industries. You'll be responsible for designing, modifying, and scaling architecture, as well as designing and implementing scalable infrastructure for AI/ML solutions and data engineering. You'll be the SPOC with the R&D team, collecting the productized components and adding and scaling these components on the platform. Architect and scale AI inference platform and related components for all data modalities like Tabular, text, image, video, etc. You'll be responsible for designing the AI Ops and AI Inferencing Ops - model building, data preprocessing, model inferencing, explainability, monitoring, alignment, risk management components. You'll work on running multiple optimizations on inference speed and latencies to serve multiple AI models - LLMs, DL models, classic ML models, etc. You'll manage product development activities, including scrum reviews and productivity optimization across engineering, as well as collaborate with R&D/data science and front-end teams. You'll mentor and guide juniors and middle managers. You'll continuously improve the standards of the product, as well as the architecture, culture, and experience. What You’ll Get Highly competitive and meaningful compensation package One of the best health care plans that covers not only you but also your family, and offers the best Life insurance plans. A great team Micro-entrepreneurial tasks and responsibilities. Career development and leadership opportunities
AryaXAI stands at the forefront of AI innovation, revolutionizing AI for mission-critical businesses by building explainable, safe, and aligned systems that scale responsibly. Our mission is to create AI tools that empower researchers, engineers, and organizations to unlock AI's full potential while maintaining transparency and safety. Our team thrives on a shared passion for cutting-edge innovation, collaboration, and a relentless drive for excellence. At AryaXAI, everyone contributes hands-on to our mission in a flat organizational structure that values curiosity, initiative, and exceptional performance. As a Senior Software Engineer, you will be a technical leader within the Platform Engineering team, responsible for architecting and implementing the most critical components of the AryaXAI platform. You will move beyond feature development to take ownership of entire systems, from initial design to production deployment and long-term reliability. Your role will involve tackling our most complex technical challenges, such as designing a cost-aware distributed job scheduler, building a high-performance AI inferencing setup or architecting our multi-cloud serverless framework. You will mentor junior engineers, drive technical decision-making, and set the standard for engineering excellence across the team. Key Responsibilities Architect and Own Core Systems: Lead the design, development, and operational ownership of large-scale distributed systems that are the foundation of our AI inferencing platform. Solve High-Complexity Problems: Tackle ambiguous and challenging engineering problems in areas like high-performance computing, distributed consensus, resource scheduling, and multi-cloud orchestration. Drive Technical Strategy: Influence the team's technical roadmap, evaluate new technologies, and make key architectural decisions that impact the entire platform's scalability, reliability, and cost-effectiveness. Mentor and Elevate the Team: Act as a technical mentor to other engineers, providing guidance through code reviews, design discussions, and pair programming, fostering a culture of high-quality engineering. Champion Best Practices: Set and enforce best practices for software development, including advanced testing strategies, CI/CD automation, system observability, and operational readiness. Performance Optimization: Profile and optimize critical system components, diving deep into performance bottlenecks across the stack, from Python code to network I/O and infrastructure configuration. Required Qualifications Extensive Experience: 5+ years of professional software engineering experience, with a demonstrated track record of designing and delivering complex backend systems. Expert in Python and have built scalable systems. Experience with Puppet/Chef/Ansible, Amazon Web Services (AWS), Git, Graphite and related tools for large-scale systems management is a must. Expert-Level Python: Deep, idiomatic knowledge of Python. This includes advanced concepts like asynchronous programming (asyncio), concurrency models (multithreading/multiprocessing), the Global Interpreter Lock (GIL), and experience with performance profiling and memory optimization tools. Proven System Design Skills: Demonstrable experience architecting scalable, fault-tolerant, and highly available distributed systems. You should be able to fluently discuss the trade-offs of different architectural patterns (e.g., microservices vs. monoliths), data consistency models (e.g., eventual vs. strong), and communication protocols (e.g., REST, gRPC, message queues). Deep Cloud And Distributed Systems Knowledge Cloud Infrastructure: Hands-on experience building and deploying production workloads on at least one major cloud provider (AWS, GCP, Azure). Messaging & Queuing: Practical experience with message brokers like RabbitMQ or Kafka for building asynchronous, event-driven systems. Caching Strategies: In-depth knowledge of caching patterns and hands-on experience with systems like Redis or Memcached. Database Expertise: A strong understanding of the trade-offs between SQL and NoSQL databases and experience designing data models for performance and scale. Mastery Of Containerization And Orchestration Docker: Expert-level understanding of Docker, including multi-stage builds, image optimization, and container networking. Kubernetes: Deep, hands-on experience managing production applications on Kubernetes. This goes beyond deploying simple services and includes understanding the Kubernetes control plane, writing custom controllers/operators, and configuring networking (CNI), storage (CSI), and security policies. Preferred Qualifications High-Performance Computing (HPC): Experience writing or integrating with performance-critical code using lower-level languages like C++, Go, orRust. Building Developer Platforms: Experience building internal developer platforms (IDPs), custom schedulers, or orchestration frameworks from the ground up. AIOps and AI Infrastructure: Familiarity with the AIOps lifecycle and experience with tools like Kubeflow, MLflow, or building model inference servers (e.g., Triton, TorchServe, or custom vLLM/SGLang implementations). Advanced Kubernetes: Experience with service meshes (e.g., Istio, Linkerd) and building custom CRDs and Operators to extend Kubernetes functionality. Multi-Cloud and Serverless Architecture: Direct experience designing and implementing systems that span multiple cloud providers or building custom serverless platforms. What’ll You Get Highly competitive and meaningful compensation package One of the best health care plans that covers not only you but also your family A great team Micro-entrepreneurial tasks and responsibilities. Career development and leadership opportunities