Giga builds AI agents trusted by the largest B2C companies in the world. Industry leaders like DoorDash rely on Giga to automate their most complex support and operations workflows across voice, chat, and email.
Our mission is to help enterprises deliver faster, smarter, and more human customer experiences at scale - powered by AI that actually works in production.
We’re an in-person team based in San Francisco, with remote presence in New York and London - operating with speed, precision, and a deep sense of ownership. Backed by top-tier investors and operators, including a $61 million Series A round led by Redpoint Ventures with participation from Y Combinator and Nexus Venture Partners, Giga is scaling quickly across some of the most recognizable consumer brands in the world.
We’re looking for a seasoned Solutions Engineer to join Giga’s founding team. In this role, you’ll collaborate closely with Sales, Forward Deployed Engineering, Product, and Core Engineering to help the world’s largest brands operationalize AI agents that transform customer experience and support operations.
As a founding Solutions Engineer, you’ll lead complex, multi-stakeholder engagements that span pre-sales strategy, solution architecture, deployment execution, and long-term customer success - combining sharp commercial acumen with deep technical expertise to design and deliver solutions that drive measurable business impact. You’ll bring a deep sense of curiosity, an eye for precision, and a drive to tackle hard, ambiguous problems. Turning vision into reality for some of the most recognizable brands in the world.
Own strategic technical relationships: Build deep, trusted partnerships with technical executive stakeholders across CX, Operations, and Product teams.
Drive growth across key logos: Partner with the account team to drive expansion within our largest customers and convert POCs into multi-year, multi-million-dollar partnerships.
Co-own implementation: Manage timelines, integrations, and deliverables across forward-deployed, product, and engineering teams.
Influence product direction: Translate customer feedback and emerging use cases into roadmap insights and feature priorities.
Shape the foundation: Help define team culture, processes, and best practices as a founding member of the Solutions organization.
Experienced solutions engineer with enterprise selling experience (4+ years in strategic or enterprise SaaS): You bring a track record of working across large, multi-stakeholder enterprise organizations, engaging senior business and technical leaders, and navigating complex sales cycles.
Strong communicator and trusted advisor: You can translate complex technical solutions into business value that resonates with executives, and build credibility with both customers and internal teams - think product, engineering, success, sales, etc.
Comfortable operating with ambiguity: You excel in early-stage, high-growth environments where structures aren’t always fully defined, and you’re motivated by continuous improvement - sharing best practices, building reusable playbooks, and helping define the foundation of the Solutions organization.
Solid technical foundation: You have experience working with Python, APIs, data pipelines, cloud infrastructure, or full-stack engineering contexts, and you’re ready to deepen that into enterprise-scale AI agent deployments.
Early GTM or founding solutions or forward-deployed experience at a fast-growing startup, preferably at an AI company.
Experience selling AI, automation, or CX transformation solutions into enterprise companies and familiarity with large-scale deployments.
Working software engineering experience and a deep interest in all things AI - trends, companies, technologies.
Competitive base + commission + equity
Full health, dental, and vision coverage
On-demand snacks, coffee, and DoorDash Credits
Equinox membership
Uber rides home when working late
15 days of accrued PTO + 5 sick days
$200-$300k OTE (based on experience)
Remote
Stage 1 - Recruiter screen (30 min)
Stage 2 - Hiring manager interview (45 min)
Stage 3 - Virtual presentation interview (1.5 hr)
Stage 4 - In-office onsite exercise and team interview (3 hours)
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