AI Solutions Lead, Marketing

At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers.

Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table.

There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work.

Most companies are layering AI onto existing processes. This role is about something different: rebuilding those processes from the ground up, so teams can do work that actually matters.

Instacart's Marketing team has set ambitious AI goals — and this is the person who makes them real. You'll be the first role of this kind in Marketing, embedded in the org with a clear mandate: identify what's slow, manual, or broken across the Marketing organization and rebuild it into something fundamentally better. The benchmark isn't marginal improvement. It's transformation — building solutions that make people wonder how they ever worked without them.

This is a builder role. Strategy is a means to an end. The end is something shipped, adopted, and measurable. You'll also be the connective tissue for Marketing's AI ambitions — convening the people who own AI goals, unblocking what's stuck, and creating internal momentum that makes the whole org move faster.

Building (60%)

• Identify high-impact workflows, systems, and processes across Marketing that are slow, manual, or duct-taped together — and rebuild them AI-natively, from the ground up
• Own the full cycle: understand the current state, design the solution, build it, ship it — then measure what changed. Establish the before, prove the after, and make the case to leadership
• Walk in with work already queued. Early builds include:
• Recurring leadership and planning narratives — transforming how Marketing produces its MBR, quarterly planning summaries, budget variance write-ups, and channel performance narratives; currently manual synthesis across multiple inputs, rebuilt into a faster, more consistent, AI-native output
• Integrated campaign launch process — automating key steps from campaign ideation to launch, reducing the manual handoffs and coordination overhead that slow campaigns down across teams
• Brief quality and standardization — an AI review layer that evaluates briefs before they leave the building, flags what's missing or unclear, and raises input quality across the org before downstream teams absorb the cost of a bad brief
• Build with portability in mind — your solutions should be constructed so others can pick them up, adapt them for their own context, and extend what you've built without starting from scratch; you're not just solving a problem, you're creating infrastructure others can build on
• Develop and maintain an intake framework: gather inputs from across the org, evaluate feasibility and impact, and make a defensible call on what gets built next — including what doesn't; prioritization discipline means saying no to low-value requests as readily as yes to high-value ones

Driving Adoption (20%)

• Own the change management side of every build: create the conditions for people to trust what you've built, use it consistently, and not revert to old habits when something feels unfamiliar
• Evangelize internally — write up wins, build case studies, show other teams what's possible; your goal is to generate more demand than you can supply, which means the org needs to see what AI can actually do, not just hear about it
• Create energy around AI across Marketing — not as a cheerleader, but as someone who shows people things they didn't know were possible and makes it easy for them to take the next step

Orchestration & Thought Partnership (20%)

• Lead the MarComms AI KR forum: convene AI KR owners across Marketing, create momentum behind shared goals, surface blockers, and hold the operating cadence
• Act as a working partner to AI goal owners — unblocking vendor delays, solving capability gaps, helping people get unstuck

• 7+ years in marketing operations, marketing strategy, or a closely adjacent discipline — you understand how marketing orgs work, where the friction lives, and what it costs to leave it unfixed
• Proven builder with a track record of impact — you have shipped AI-powered workflows and processes that demonstrably changed how teams work; you can name the problem, describe the solution, and quantify the result.  You’re so invested in AI that you’ve applied it beyond the scope of your current role.
• Hands-on daily experience with frontier AI tools such as Claude, GPT-4o, or Gemini, including writing prompts that produce reliable, production-quality output at scale
• Experience building agentic systems where AI components interact with each other, including multi-agent design, orchestration layers, and workflows that run without a human in the loop at every step
• An adoption-minded approach to building: designing for adoption from day one and taking accountability for whether what you built actually gets used
• Strong communication skills, with the ability to explain what you're building, why it matters, and where it stands, for audiences from ICs to CMO-level leadership
• Prioritization discipline — you can evaluate a request and tell someone their problem isn't a good AI candidate right now, or that the cost of building outstrips the benefit; you know what not to build

Optional garnishes (Preferred Qualifications)

• A framework for evaluating AI vendors and tools quickly, including running comparison pilots and making principled decisions about what earns a place in the stack