Staff Engineer, AI & Data Platform

Inktavo

10h • $150,000 - $175,000 • Remote

About The Position

The Shared Technology team is responsible for the platforms, services, and infrastructure that power intelligent, connected experiences across our entire portfolio: unified analytics, shared data services, a UI component library, AI-native tooling, and more. As a Staff Engineer with AI & Data Platform focus, you won't just write code - you'll shape the technical foundation that the rest of engineering builds on. You'll architect and deliver the systems that make our products smarter, faster, and more data-driven. You'll partner closely with Product leaders to translate business strategy into technical execution, set the engineering bar for cross-platform AI and data work, and guide how agentic AI is integrated into our products and development workflows. If you're energized by greenfield problems, care deeply about engineering craft, and want to work somewhere your technical decisions have organization-wide impact - this role was written for you.

Requirements

• 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.

Nice To Haves

• 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.

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.

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

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed