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Avante

Solutions Engineer

Reposted 3 Days Ago
In-Office
New York, NY, USA
175K-200K Annually
Mid level
In-Office
New York, NY, USA
175K-200K Annually
Mid level
As Avante's first Solutions Engineer, you will support enterprise sales by leading technical discussions, conducting demos, and engaging with various stakeholders to ensure solution fit and compliance requirements are met.
The summary above was generated by AI

The Role

    This is Avante’s first Solutions Engineer hire. You will partner closely with Sales to lead the technical side of the deal across the enterprise sales cycle.

    You will be involved from technical discovery through final validation, helping customers understand how Avante works, how it fits into their environment, and why it meets their security and compliance requirements. This includes deep involvement in demos, solution design, and technical diligence with enterprise stakeholders.

    Avante sells into complex organizations with multiple stakeholders, including HR, finance, and CIO and security teams. You need to be comfortable navigating those conversations, translating technical concepts clearly, and representing the product with credibility.

    This is a highly cross-functional role. You will work closely with Sales, Product, Engineering, and Customer Success to ensure technical accuracy, strong deal execution, and a clear path from evaluation to deployment.

What You'll Own

    Technical deal execution
    Partner with Account Executives throughout the sales cycle. Lead technical discovery, participate in solution validation, and support deals through final stages including security and compliance review.

    Demos and solution design
    Prepare and deliver tailored demos based on customer needs. Define the demo path, highlight relevant use cases, and adapt to both technical and non-technical audiences.

    Security, data privacy, and AI compliance conversations
    Handle technical diligence across InfoSec, data privacy, and AI compliance. Engage confidently with stakeholders evaluating risk, architecture, and regulatory considerations.

    Architecture and product understanding
    Develop a strong understanding of Avante’s technical architecture, infrastructure, and data model. Translate how the system works into clear, customer-facing explanations.

    Partner and channel support
    Support broker and partner-led deals. Participate in joint sessions, technical walkthroughs, and customer-facing engagements where partners are involved.

    Late-stage deal support
    Contribute to RFPs, security questionnaires, and final validation steps. Help ensure technical confidence in Avante as a chosen solution.

Who You'll Partner With

    Sales on deal strategy, discovery, and execution
    Customer Success on deployment expectations and handoff context
    Product and Engineering on technical accuracy and product feedback
    Partners including brokers and consultants bringing Avante into enterprise accounts

What We're Looking For

    Experience supporting enterprise sales cycles in a customer-facing technical role
    Experience selling into CHRO, CFO, or CIO organizations
    Experience in HR tech, benefits, healthcare, or insurance

    Strong technical foundation with the ability to explain architecture, infrastructure, and data concepts clearly
    Familiarity with cloud infrastructure and modern data systems
    Working knowledge of modern AI systems and how they are deployed in enterprise environments
    Familiarity with security, data privacy, and compliance considerations in enterprise software
    Ability to communicate effectively with both technical and business stakeholders
    Comfort operating in a fast-moving, early-stage environment
    Strong collaboration skills across Sales, Product, and Engineering

     

    Nice to Have:

    Experience supporting partner or channel-led sales motions
    Background in early-stage or category-creating companies 

How We Work

    Our four values aren't aspirational. They translate into concrete operating tenets that shape how we make decisions every day.

    Beat Yesterday. We re-evaluate our own toolkit every quarter, because the workflows that made you effective three months ago may already be outdated. We act on 70% of the information rather than waiting for certainty. We timebox, execute, and iterate, getting work in front of real people quickly instead of polishing in isolation. And we own our output regardless of how we produced it. AI can get you 80% of the way there. Everything that goes out with your name on it is your responsibility to review, refine, and stand behind.

    Embrace Type 2 Fun. We take on hard problems and find meaning in the work, even when it's uncomfortable. We assume good intent and follow up directly rather than venting in side channels. We celebrate wins loudly and specifically, naming the actual behavior so the whole team learns what great looks like. We are on by default, because we owe it to each other and to our customers to be available beyond what a regular corporate job would demand. And we do unscalable things today that build scalable advantages tomorrow: every white-glove implementation, every hand-built QBR deck, every late-night RFP turnaround earns us the right to scale later.

    Stay Hungry, Stay Curious. We expect everyone to be the expert on AI in their function before anyone asks them to be. The landscape changes weekly. When you learn something, teach it. Learn enough about adjacent functions to ask good questions. Ask the question you think is too basic, because in complex domains like benefits, the cost of a wrong assumption can be a lost account. And remember: curiosity without urgency is a hobby. Learning has to translate into action on a timeline that matches the opportunity.

    Act Like an Owner. We say the uncomfortable thing early, raising missed commitments or quality gaps directly with the person within 48 hours. We surface problems when they're small, not the week they become a crisis. Customer-facing work gets priority, always. And we close the loop every time, because over-communication is a feature at our stage, not a bug.

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