Summary:We're looking for a Staff Pre-Sales Solutions Engineer: a senior individual contributor who leads by example on our largest and most complex US deals. Anaconda is building a vendor-neutral way for enterprises to adopt AI at scale, and recent acquisitions have expanded our capabilities. You'll own the technical win, show senior technical and business buyers how our products work together, and build the demos, prototypes, and playbooks the rest of the team learns from. This role is for a builder who likes creating solutions from scratch.
What You'll Do:- Own the technical win on strategic, multi-stakeholder enterprise evaluations, from discovery and solution design through proof-of-concept and technical close
- Hold the room with senior buyers (CIOs, CDOs, heads of data science and platform engineering, security and procurement) and connect Anaconda's products to their business outcomes and architecture
- Tell the combined Anaconda story, showing how our products work together to give enterprises a vendor-neutral way to adopt AI
- Build working prototypes, integrations, and agentic demos from scratch to prove out new use cases, and turn the best of them into reusable assets
- Partner with sales directors and VPs on deal strategy for the most complex and competitive opportunities, and help define win criteria and evaluation standards across segments
- Build the demo environments, evaluation plans, competitive positioning, and technical content the wider GTM team adopts, and get yourself expert on new and acquired products quickly and help bring the team along
- Spot and name problems leadership hasn't framed yet (product gaps, competitive threats, patterns in why deals are lost) and drive them to a commitment with product, engineering, and marketing
- Lead by example on your own deals, share what's working in deal reviews and joint calls, and be the person other SEs and members of the GTM org turn to when an evaluation gets hard
- Set the standard for responsible, effective use of AI in pre-sales work, including knowing when not to use it
Your Impact will be measured through:- Technical win rate on strategic and enterprise opportunities where you own the technical evaluation
- Deal size expansion through identification of additional use cases, products, and buyers
- Sales cycle velocity on complex deals with your technical engagement
- Adoption of the demo assets, evaluation plans, and playbooks you create across the SE team
- Product and go-to-market changes driven by the customer and competitive insight you bring forward
- Quality of customer handoffs to post-sales teams that set accounts up for successful implementation and expansion
What You Need:- 8+ years in customer-facing experience in technical roles such as solutions engineering, sales engineering, solutions architecture, or technical consulting, including significant time leading enterprise technical evaluations
- Deep hands-on experience with tools and workflows in AI, data science, or data engineering, enough to design solutions, run proof-of-concepts, and go deep with practitioners and architects
- Hands-on experience building with agentic AI (coding agents, LLM APIs, MCP, or similar), and the judgment to explain where it fits in an enterprise
- A track record of winning complex, multi-buyer enterprise deals against competitors, with you as the technical lead
- Credibility with executive audiences, including translating technical capability into business value and handling senior technical and security objections
- Experience building assets, processes, or standards that other SEs adopted, and influencing peers without formal authority
- Based in the United States, with the ability to travel to customer sites and company events as needed
What Will Make You Stand Out:- You have deep, hands-on knowledge of one or more of the areas Anaconda's products cover, ideally from having worked in them as a practitioner:
- Secure, governed open-source Python and package management for the enterprise
- AI agents and agentic coding, including governance, cost, and privacy at scale
- ML orchestration and MLOps: building, scaling, and deploying ML and AI workflows in production
- AI guardrails and security for LLM and agent applications
- You've sold or architected enterprise software in regulated industries such as financial services or the public sector
- You've helped bring acquired or newly launched products to market as a technical lead
- You have prior experience at a fast-paced startup where you adapted quickly to changing priorities and wore multiple hats to drive results
- You've worked directly with open-source tools or contributed to open-source communities, giving you insight into how developers evaluate and adopt tools
- You embody our values: 'Curious by Default', 'Build Together', 'Own It', and 'Lead with Guts and Heart', and our behaviors: Clarity, Care and Candor
- You care deeply about fostering an environment where people of all backgrounds and experiences can flourish
- Experience working in an open-source, AI, or data science-oriented company
Why You'll Like Working Here:- You'll thrive in a high-performance environment where results are recognized and rewarded
- Your work directly contributes to shaping the future of data science, machine learning, and AI in the enterprise.
- You'll work alongside a collaborative team that values diverse, thoughtful discussion, clarity and candor.
- You'll be supported by a culture that puts employees first - with flexible hours, a fully remote setup, and a genuine commitment to your wellbeing and growth.
We accept applications on an ongoing basis.
In addition to base salary, we offer a comprehensive benefits package that includes:
- Office setup reimbursement
- Monthly productivity stipend
- Learning and Development reimbursement
- Open vacation policy*
- Public holidays
- Snake Days-quarterly extra day off company wide
The application deadline for this role is 12/27/2026; applicants will be reviewed on an ongoing basis until the role is filled.
The US base salary range for this role is $140,000-$200,000 + variable commission structure based on sales performance + equity + benefits. Our salary ranges are determined by role, level, and location.
