Lead Solutions Engineer
Posted Updated
- As a Senior Solutions Engineer focused on enterprise pre-sales, you are the technical bridge between our enterprise prospects and our AI-powered decisioning platform. You will partner with the Sales Team to architect AI-driven solutions for the world’s most innovative financial institutions
- You help scale the impact of the Solutions function by creating reusable collateral, establishing solution patterns, and mentoring others on customer engagement and technical strategy
- You discover and translate customer’s strategic priorities and problem statements into high impact Agentic AI use cases leveraging Taktile during the sales process and throughout the Enterprise sales cycle, focusing on uncovering high-value AI use cases that justify significant investment and strategic partnership
- You lead the design and execution of proof-of-value projects that combine customer data, ML/AI models, and Taktile’s platform to demonstrate strategic ROI. You build technical prototypes and demos leveraging the Taktile platform that simulate production-grade integrations and workflows
- You collaborate with partners and customers to design and build solutions in Taktile’s Agentic Decisioning Platform
- You lead proof-of-value projects and can communicate the value opportunity of a full implementation and the corresponding strategic roadmap to senior stakeholders up to C-level executives
- You work with product management to share competitive intelligence and prospect insights gathered during the sales process, helping shape Taktile’s AI product roadmap and positioning strategy
- You create re-usable collateral, best practices & tools to help scale your knowledge and expertise across the solution engineering function
- You lead the discovery for new use cases and implement them on the platform to assess product-solution fit. You provide feedback to our product team and share results of your discovery with go to market functions
- You are collaborative and work well with your peers in Marketing, Sales, Product, Engineering and the Customer Success team
- You have a proven track record of supporting high-contract-value enterprise deals. You understand that winning an enterprise deal requires more than just good code—it requires strategic positioning, deep discovery, and the ability to handle complex technical objections.”
- You are open to a hybrid work model and can work from our NYC office at least three days per week
- You are curious and customer-centric. You enjoy learning about our customers’ and prospects’ businesses and helping them solve challenges
- You have 3+ years of hands-on experience writing production Python code
- You excel at navigating complex Enterprise organizations with stakeholders across different levels of seniority and including both technical stakeholders in an organization (e.g. Principal Engineers, Data Scientists) as well as business stakeholders (e.g. Risk Managers, Credit Analysts)
- You are humble and have a growth mindset, with a willingness to learn new skills and methodologies and bring best practices into our business
- You are able to plan and manage the technical scope of Proof of Concepts (POCs) and technical evaluations. You excel at managing multiple high-stakes prospects simultaneously while partnering with Sales to drive deals to close
- You have experience operating in a technical leadership role—whether by owning strategic accounts, mentoring junior team members, or shaping solution strategy at scale in a high-growth environment
- Live for Customer Value: You have at least 5-7 years of experience working within Enterprise Solution/ Sales Engineering in B2B SaaS, or in a senior technical consulting role
- Technical expertise: You have a general understanding of REST APIs (design, integration, authentication)
- You have experience building, tuning, or deploying ML models (e.g., scikit-learn, XGBoost, PyTorch, TensorFlow) in production settings
- You are comfortable explaining how a model works to both a technical stakeholder such as a CTO and domain experts such as Credit Risk Managers
- Experience with AI use cases in financial services (e.g. fraud detection, credit scoring, underwriting) is a strong plus
- You have acquired domain expertise in the financial services industry (banking, insurance, capital markets, payments, etc.)