Jobs at Modus Create

Build and operate reliable, observable backend systems across AWS and Python services. Responsibilities include defining SLOs and error budgets, designing monitoring and alerting, managing incident response and 24/7 on-call rotations, conducting postmortems, improving performance and capacity, automating toil reduction, maintaining infrastructure as code and deployment pipelines, and mentoring SRE engineers. The role also involves consulting with client teams, documenting operational practices, and supporting AI workloads.

Leads client-facing database migration and modernization engagements across AWS, relational, and NoSQL platforms. Designs migration architectures, data pipelines, ETL/ELT workflows, proof-of-concepts, and reusable technical accelerators. Facilitates executive conversations and workshops, translates complex technical solutions into business outcomes, and supports pre-sales opportunities. The role also develops GenAI-enabled migration tooling, influences senior stakeholders, and collaborates with distributed engineering, product, and data teams.

Design and deliver cloud-native data platforms, scalable big data pipelines, lakehouses, warehouses, transformation frameworks, BI solutions, and ML-enabled data workflows. Lead client-facing pre-sales engagements, technical workshops, proof-of-concepts, executive conversations, and enterprise data modernization initiatives. Build reusable architectural IP, influence senior stakeholders, and translate ambiguous business challenges into production-ready solutions using AWS and modern data technologies.

Lead digital product delivery for client teams from problem framing through release and adoption. Responsibilities include discovery, requirements, prioritization, backlog and story management, stakeholder alignment, risk and dependency management, cross-functional collaboration, and defining success metrics. The role independently guides product decisions across engineering, design, quality, business, and delivery teams in complex consulting environments.

Design and ship end-to-end digital product experiences through research, workflows, interaction design, prototyping, responsive interfaces, and design systems. Collaborate directly with clients, product managers, engineers, researchers, content designers, and quality specialists from product shaping through implementation, release, and iteration. Use analytics, user feedback, usability testing, and AI-assisted tools to improve products and delivery practices.

Lead end-to-end product design for complex digital products in a client-facing consulting environment. Translate ambiguous challenges into product models, workflows, interfaces, coded prototypes, and production-ready implementation context. Collaborate directly with executives, users, product teams, and engineers while using AI-assisted development tools, Figma, and modern frontend technologies. Stay engaged through implementation, design QA, release, and iteration.

Lead enterprise-scale migrations to GitHub Enterprise Cloud, including repositories, users, access controls, workflows, Enterprise Managed Users, and data residency. Build governed identity and access environments, validate integrations, and document handoffs. Design and maintain scalable internal developer platforms, standardize tooling, and develop self-service infrastructure and CI/CD capabilities. Partner with client IT teams, mentor engineers, and apply cloud-native architecture, Kubernetes, automation, and Infrastructure as Code practices.

Design, build, and deploy production-ready intelligent solutions using machine learning, deep learning, generative AI, and large language models. Develop RAG pipelines, integrate AI services, manage model deployment and MLOps workflows, and apply strong software engineering practices. Collaborate with engineering, product, and data teams in a distributed environment to create scalable, reliable, responsible AI-powered products.

Build and deploy AI-powered applications for customers, combining Python and TypeScript application engineering with LLMs, generative AI, agent orchestration, APIs, distributed systems, and cloud platforms. Partner with stakeholders to understand requirements, design scalable architectures, rapidly prototype solutions, integrate AI capabilities, and evolve proofs of concept into production systems. The role also involves customer-facing consulting, technical decision-making, and collaboration throughout the solution lifecycle.