Join a forward-thinking technical go-to-market team helping businesses navigate the next generation of AI-powered software purchasing. As a Lead Solutions Engineer, you will combine customer-facing technical expertise with hands-on solution building to demonstrate how an AI-enabled customer platform can deliver measurable business outcomes.
Compensation
Annual cash compensation range of $132,400–$189,100 USD, including base salary and applicable on-target commission or annual bonus targets. Potential eligibility for equity compensation through restricted stock units (RSUs), depending on role and compensation arrangements.
Responsibilities
Lead customer discovery sessions to uncover business challenges, desired outcomes, technical requirements, and opportunities for improvement.
Create compelling, outcome-focused demonstrations and product experiences that show how an AI-powered customer platform can transform business operations.
Partner with Account Executives to understand technical buying committees, assess competitive environments, and develop effective paths toward purchasing decisions.
Translate complex legacy systems into streamlined, scalable solution architectures that integrate with customers' wider technology ecosystems.
Design and rapidly build functional proofs of concept using AI coding tools, AI agents, and developer frameworks, with clear use cases, success criteria, and timelines.
Design and own the backend infrastructure supporting sales and business development teams, turning fragmented workflows into reliable, scalable systems.
Compensation
Annual compensation of approximately USD 20,000–32,000, depending on location and experience.
Responsibilities
Design and build data pipelines that collect account and contact information from multiple sources and APIs, clean and deduplicate records, calculate scores, and synchronize data with the CRM as a reliable source of truth.
Develop and maintain the central data model and database connecting CRM, outreach, and product information.
Build integrations between internal and third-party platforms using REST APIs and webhooks.
Develop lightweight internal services and tools whenever existing solutions do not adequately meet business needs.
Create signal detection, lead-scoring, routing, and alerting systems that help sales representatives identify the right accounts to prioritize and understand why they matter.
Requirements
Degree in Computer Science or a related engineering discipline
Own and lead the backend systems behind Epic's CI/CD and build tooling, focusing on software supply chain security and cloud infrastructure.
Locations (2)
California, United States
Washington, United States
Compensation
The expected annual base pay range(s) for this position are detailed below. Each base pay range is relevant only for individuals who are residents of or will be expected to work within the specified locale. Compensation varies based on a variety of factors, which include (but aren’t limited to) things such as skills and competencies, qualifications, knowledge, and experience. In addition to base pay, most employees are eligible to participate in Epic’s generous benefit plans and discretionary incentive programs (subject to the terms of those plans or programs).
Responsibilities
Design, build and operate the backend infrastructure for our CI/CD and artifact platforms on AWS and GCP
Lead software supply chain security work, including vulnerability scanning, artifact signing and provenance, and hardening of build runners and agents
Partner with security and governance teams on controls, audits and compliance requirements, and turn them into practical changes to tools and pipelines
Take the EDL vision and high architecture as defined, turn it into concrete low-level designs, work packages, explain and hand them to the engineering team, and work with the project managers to deliver on phase deadlines. Hands on ~ 50%, deep enough to review, unblock and set the technical bar. Owns outcomes end to end, finds and fixes problems, and multiplies that reach with AI native way of working.
Compensation
A Competitive pay, the salary range for the role is $135,000 - $145,000.
Responsibilities
Translate vision into design. Take the architectural direction and produce implementable designs, strategize and translate to tasks. Keep the vision and high-level design intact through delivery without redefining the vision or reducing the scope.
Build with AI every day using Claude Code, Codex or similar. Write the markdown specs, skills and context files that make coding effective, and review what they produce to a production standard.
Stay hands on with the Data Lakehouse foundation. Python, PySpark, Delta Lake and medallion design on AIDP (OCI).
Design data products and semantic structures. Blueprints covering scope, canonical entities, certified metrics, quality rules, lineage, access and publication criteria.
Set standards for keys, naming conventions, configuration, reference data and metadata, and keep them aligned to the business glossary.
Senior Software Engineer to serve as the forward deployed engineer for the firm's Finance organization, building production software on Vista's AI platform.
Compensation
The annualized base pay range for this role is expected to be between $95,000 - $180,000. Actual base pay could vary based on factors including but not limited to experience, subject matter expertise, geographic location where work will be performed and the applicant’s skill set. The base pay is just one component of the total compensation package for employees. Other components may include an annual cash bonus and a comprehensive benefits package.
Responsibilities
Embed with Finance as its dedicated engineer
Turn loosely defined finance problems into product requirements and design documents
Design, build, and operate finance applications, automations, and AI experiences end to end on Vista's platform
Partner with Finance Technology's department technologists
Bring the most useful finance apps built by business users onto Vista's enterprise platform
Design, build, and operate AI applications and platform services end to end, from early discovery through production support.
Locations (2)
Austin, Texas, United States
United States
Compensation
The annualized base pay range for this role is expected to be between $140,000 - $260,000. Other components may include an annual cash bonus and a comprehensive benefits package.
Responsibilities
Design, build, and operate AI applications and platform services end to end, from early discovery through production support.
Engage business users to identify the real problem, write product requirements and design documents, and break work into deliverable pieces.
Use modern AI tooling throughout delivery while holding all shipped code to a high bar of review and quality.
Lead user testing, rollouts, and go-lives with business owners, managing scope, tradeoffs, status, and adoption directly.
Own shipped software, including releases, defects, and ongoing iteration.
Hands-on operations role focused on identifying bottlenecks, designing, and building AI-driven automations for internal company tools like lead assignment, agent management, and commission processing.
Compensation
Base salary range: CAD $90,000 to $180,000, with the final offer based on skills and experience.
Responsibilities
Identify operational bottlenecks
Design and build AI-driven automations to replace manual work
Write and commit code on internal tooling using AI coding tools
Set and track success measures for changes (hours saved, error rate, turnaround time)
Pull and read data (SQL, dashboards) to inform fixes
Join a B2B AI team at the intersection of sales, product, engineering, and insurance brokerage customers. You will lead technical pre-sales work and customer deployments, helping prospects see value while shaping how the platform is configured and adopted.
Compensation
Base salary: $150,000 to $200,000 annually.
Responsibilities
Partner with sales representatives to design and deliver customer pilots that demonstrate product value.
Translate insurance workflows into extensible Python scripts, agent skills, and deployment architecture.
Configure and validate integrations with agency management systems, CRMs, carrier portals, and other data sources.
Lead technical discovery, demos, and deployments, supporting customer enablement and adoption.
Share customer feedback with product and engineering teams to inform the roadmap.
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