[Remote] Staff Engineer, AI & Data Platform

Note: The job is a remote job and is open to candidates in USA. Inktavo is a company focused on modernizing the apparel and promotional product decoration industry through innovative technology. They are seeking a Staff Engineer with a focus on AI & Data Platform to architect and deliver systems that enhance product intelligence and efficiency, while collaborating with Product leaders to align technical execution with business strategies.

Responsibilities

• Architecting the data platform: Designing and building the ingestion pipelines, data models, and serving layer that power embedded reporting, operational dashboards, and AI-ready data products across our suite of products
• Driving agentic AI integration: Exposing APIs across our portfolio as tool calls for LLM-driven workflows, building the agentic platform that handles cross-product concerns, and guiding how AI agents are woven into our SDLC
• Delivering shared services: Designing and implementing shared backend capabilities - inventory management services, customer data services, shared UI components - that product teams build on rather than rebuild themselves
• Partnering with Product leadership: Sitting in strategy sessions to deeply understand business goals, then translating them into technical architecture, scoped work, and accurate estimates that the team can execute against
• Setting engineering standards: Writing RFCs, leading design reviews, and establishing the patterns, tooling choices, and best practices that guide how the broader engineering organization builds on shared infrastructure
• Mentoring engineers: Acting as a technical resource and force-multiplier for other engineers - reviewing code, unblocking complex problems, and raising the technical craft of the team around you
• Evaluating and integrating AI tooling: Researching and making opinionated recommendations on AI/ML frameworks, agent orchestration tools, and data infrastructure that will power customer-facing ML capabilities
• Building with many stacks: Working across cloud platforms and codebases in whatever language the problem calls for - this role requires comfort moving between environments, not loyalty to a single stack

Skills

• 7+ years of software and data engineering experience, with a demonstrated track record of owning and delivering complex, production-grade systems end-to-end
• Shared platform / platform engineering experience: You've built infrastructure or services that multiple teams or products consumed - not just one-off features for a single team
• AI-native mindset and practical AI/ML experience: Hands-on experience building data foundations for ML workloads, integrating LLMs into product systems, or designing pipelines that feed AI/ML models. You think about AI not as a future concern but as a present engineering requirement
• Data engineering depth: Strong command of pipeline architecture, data modeling, cloud data warehousing, and orchestration - you can design a reliable, scalable, multi-tenant data platform from the ground up
• Full-stack versatility: Comfortable writing production code in multiple languages and across cloud platforms. You pick the right tool for the job rather than defaulting to what you know
• Staff-level technical leadership: You operate as an architect and tech lead - writing RFCs, driving cross-team alignment, setting technical direction - without needing formal authority to make it happen
• Product-engineering partnership skills: Experience working directly with Product leaders to understand business strategy, shape roadmaps, scope and estimate work, and keep technical execution aligned with business outcomes
• Strong written and verbal communication: Able to explain complex technical trade-offs to non-technical stakeholders and produce documentation that makes your systems understandable and maintainable
• Experience mentoring or developing other engineers at a senior or staff level
• Hands-on experience with embedded analytics in customer-facing SaaS products - building reporting features users interact with directly, not just internal BI
• SaaS platform background, particularly with multi-tenancy: building shared services that isolate customer data and scale across many client organizations simultaneously
• Familiarity with data governance tooling - catalogs, lineage tracking, access control frameworks, PII handling patterns
• Experience with eCommerce, B2B SaaS, or branded merchandise technology

Benefits

• Competitive benefits
• Unlimited PTO
• Remote work available for U.S.-based candidates
• 401(k) with employer match
• Paid parental leave
• In-office benefits for those local to Dallas, TX: catered lunches, casual office atmosphere & located in the Design District, fully stocked kitchen

Company Overview