Jobs at Evolver

Architect and improve enterprise AI platform availability, resilience, scalability, performance, and cost efficiency. Define measurable requirements, design failover and recovery mechanisms, lead capacity and performance planning, optimize AI infrastructure economics, eliminate bottlenecks, and drive production readiness across Engineering, Cloud Infrastructure, DevOps, QA, and AI teams.

Lead procurement strategy, vendor negotiations, and contract lifecycle management; run end-to-end RFP/RFI and complex deal processes; partner with product and engineering to design AI-enabled procurement solutions; support sales and client demos; manage vendor onboarding, client due diligence, and cross-functional initiatives to scale procurement capabilities.

Owns tax accuracy, quality, and performance for AI-powered Sales and Use Tax products. Translates complex indirect tax requirements into product specifications, testing strategies, evaluation frameworks, and roadmap priorities. Partners with Product, Engineering, and QA teams to deliver capabilities, investigate failures, and improve customer outcomes. Requires deep multi-state sales and use tax expertise, technology evaluation experience, strong stakeholder communication, and occasional travel.

Lead client-facing strategy and delivery for enterprise AI initiatives. Partner with customer stakeholders and technical teams to identify use cases, develop deployment roadmaps, evaluate value and feasibility, track KPIs, align stakeholders, and support rollout, adoption, and change management. The role requires structured problem-solving, business judgment, workshop facilitation, cross-functional coordination, and ownership of workstreams from discovery through deployment and value realization.

Leads enterprise AI deployment strategy and value realization across regulated functions such as finance, tax, risk, governance, and compliance. The role conducts discovery, prioritizes use cases, defines deployment roadmaps, establishes KPIs, engages executives, aligns initiatives with control frameworks, and guides deployment engineers through implementation and adoption. It requires deep regulated-domain expertise, transformation leadership, executive communication, and cross-functional stakeholder management. Travel may be required for customer engagements and workshops.

Lead the security design, architecture, and implementation for an enterprise AI platform. Define secure deployment patterns, embed security into CI/CD and operations, secure GenAI workflows, and lead customer security reviews and compliance activities for Fortune 1000 deployments.

Full-cycle recruiter for a fast-growing AI startup: own sourcing, screening, interviews, offer negotiation, and candidate experience across technical, leadership, and business roles. Partner with hiring managers, build pipelines, track hiring metrics, improve recruiting processes, and support employer branding and onboarding initiatives.

The role involves designing and deploying scalable GenAI applications using Python and cloud infrastructure, particularly Azure. Responsibilities include model optimization, mentorship of junior developers, and collaborating with teams to align AI solutions with business needs.

Develop and test AI-powered software solutions, troubleshoot challenges, and collaborate with the team to enhance performance while gaining AI experience.

Develop and deploy scalable GenAI applications, optimize LLMs, and collaborate with teams while mentoring junior developers.

The Senior Enterprise System Integrator will design, build, and maintain integrations for enterprise systems, ensuring scalability and performance across multiple environments.

Lead product strategy and execution for AI-powered enterprise solutions. Drive product development from initial concept to scaling. Collaborate with engineering, design, and customers to define and improve product-market fit.

Deliver and validate enterprise deployments of a generative-AI platform by calibrating models, building compliant decision logic, integrating customer components, running automated evaluation harnesses, and producing reusable templates to accelerate regulated, production-ready capabilities.

Design and prototype practical AI methodologies (reasoning, retrieval, agents, verification), build Python/Azure prototypes, evaluate effectiveness and failure modes, and translate validated approaches into product specifications and reference implementations while partnering with Product and Engineering.

Interns will work on data innovation projects involving data analysis, machine learning pipelines, AI systems deployment, and enterprise AI integration while gaining exposure to Fortune 500 clients.

As a Forward-Deployed Engineer, you'll deploy and integrate AI solutions for enterprise customers, troubleshoot issues, and contribute to product enhancements based on customer feedback.

The Executive Assistant & Office Manager will support leadership operations, manage executive calendars, coordinate travel, and oversee office logistics.

Lead the design, development, and deployment of scalable applications for an AI platform, while mentoring junior developers and optimizing system performance.