Jobs at Provectus

Owns partner-sourced and self-sourced enterprise sales motions for AI consulting engagements. Responsibilities include prospecting, full-cycle sales, executive relationship building, Anthropic and AWS partner management, co-selling, joint pipeline development, partner events, proposal scoping, negotiations, and closing statement-of-work deals across Financial Services and Life Sciences.

Owns partner-sourced and self-generated enterprise sales for AI consulting engagements. Responsibilities include prospecting in Financial Services and Life Sciences, managing Anthropic and AWS partner relationships, qualifying leads, running discovery through contract close, developing joint pipelines, leading business reviews, supporting co-marketing, and collaborating with architects on consulting proposals. The role requires executive-level communication, full-cycle enterprise selling, partner ecosystem development, and up to 30% travel.

Build and deploy production GenAI systems, agentic workflows, retrieval pipelines, and evaluation harnesses for enterprise customers. Work directly in customer operations to understand and redesign business processes before automating them. Write production code across backend, data, and AI layers; deploy maintainable systems on AWS; drive adoption; and own outcomes tied to business KPIs. The role requires senior technical leadership, domain adaptability, stakeholder credibility, and hands-on engineering.

Drive partner-sourced and outbound enterprise business development across Financial Services and Life Sciences. Qualify leads, conduct discovery, scope AI consulting opportunities, manage proposals and signed SOWs, maintain partner pipelines, and build relationships with AWS and Anthropic field teams. Collaborate with architects and delivery leaders, support co-selling and partner programs, and develop an enterprise client network. The role offers a path toward full-cycle enterprise sales ownership.

Build and enhance RAG systems, AI components, backend services, data pipelines, and REST APIs under senior guidance. Write production code, tests, evaluation harnesses, documentation, and runbooks. Support AWS deployments using containers and CI/CD, investigate model failures, and contribute to architecture and client handovers. The role offers increasing ownership of technical components and decisions while working in distributed, customer-facing delivery teams.

Manage office supply procurement, logistics, deliveries, vendors, invoices, payment requests, documentation, and operational needs for the Odesa office. Coordinate maintenance issues, team support, corporate events, and internal activities while ensuring timely delivery and payment of goods and services.

Own partner-sourced and self-generated enterprise sales motions for AI consulting services. Manage Anthropic and AWS relationships, qualify leads, run full sales cycles, prospect within Financial Services and Life Sciences, close consulting engagements, maintain joint pipelines, lead co-sell planning, support partner certifications and marketing, and collaborate with delivery teams on proposals. Build executive relationships and provide market intelligence to leadership.

Own growth marketing for an AI systems integrator by translating engineering work into compelling stories, videos, demos, and written content. Manage and measure channels including LinkedIn, YouTube, and X; run experiments against pipeline outcomes; and build lightweight tools, dashboards, scrapers, and microsites. The role requires strong writing, genuine AI interest, working-level Python or TypeScript skills, and comfort using AI coding tools. Candidates may be early-career and must be in New York or San Francisco or willing to relocate.

Develop and execute growth marketing for enterprise AI systems by translating technical work into compelling stories, videos, demos, and case studies. Shape company positioning, own social and content channels, build marketing tools and agentic workflows, track pipeline impact, and run experiments. The role combines strategic marketing, business storytelling, content creation, coding, and AI research.

Develops and communicates the business impact of enterprise AI systems through writing, video, demos, case studies, and digital channels. Shapes company positioning, owns LinkedIn, YouTube, X, and future channels, and runs performance-driven marketing experiments. Builds marketing tools such as scrapers, agentic case-study generators, microsites, and pipeline dashboards using Python or TypeScript. Requires strong writing, business understanding, hands-on coding, AI knowledge, and a portfolio of shipped work.

Designs and delivers production-grade GenAI solutions, including LLM applications, AI agents, RAG systems, Python services, and cloud-native architectures. Leads technical discovery, solution architecture, scoping, presales, architecture reviews, and client-facing engagements from inception through production. Mentors engineers, conducts code reviews, establishes Python engineering standards, and advises clients on architectural tradeoffs, cloud costs, testing, deployment, and AI quality assurance.

Build and enhance RAG systems, AI components, backend services, data pipelines, REST APIs, evaluation harnesses, and production AWS deployments. Write tests, investigate model failure modes, support containerized CI/CD releases, document solutions, and contribute to architecture and client handoffs. The role offers senior guidance while progressively increasing ownership of technical decisions and system components.

Owns two revenue motions: converting Anthropic and AWS partner-sourced enterprise leads into consulting clients and independently generating new business in Financial Services and Life Sciences. Responsibilities include full-cycle sales, partner relationship management, co-selling, pipeline reviews, joint go-to-market planning, executive engagement, proposal scoping, negotiations, and closing consulting statements of work. The role also requires building an enterprise decision-maker network and collaborating with delivery, architecture, leadership, and marketing teams.

Sources and qualifies new business across North America, builds and manages pipelines, conducts outbound prospecting, leads discovery conversations, and partners with leadership to close consulting and technology-services opportunities. The role targets mid-market and enterprise clients, requires independent prospecting and negotiation skills, and involves attending industry events and client meetings with approximately 40% travel.

Sources and qualifies new business opportunities across North America, builds sales pipelines, conducts outbound prospecting, leads discovery conversations, and partners with leadership to close consulting and technology services deals. The role focuses on selling AI and cloud solutions to mid-market and enterprise clients, requires independent prospecting and negotiation skills, and includes attendance at industry events and client meetings with approximately 40% travel.

Own full-cycle recruiting for forward-deployed engineering and leadership roles across the US. Source passive AI and technical talent through LinkedIn, GitHub, communities, referrals, and talent mapping. Build Provectus’s talent community through meetups, workshops, hackathons, university programs, and industry events. Partner with hiring managers and senior leadership on hiring criteria, workforce planning, compensation benchmarking, candidate experience, and offer negotiation.

Build and deploy production GenAI systems, agentic workflows, retrieval pipelines, and data services for enterprise customers. Learn operational domains firsthand, redesign business processes, create evaluation harnesses, write production Python or TypeScript, and deliver observable AWS-based systems. Partner with executives, engineers, and operators to drive adoption and measurable business outcomes while contributing reusable industry blueprints.

Design and implement cloud-native AI solutions, build relationships with clients, and optimize AI systems. Mentor others and lead architecture decisions.

Embed with customers to learn their workflows, design and ship production GenAI/LLM solutions on AWS, build eval suites, operate and iterate systems, and partner with senior stakeholders to drive measurable business outcomes.

Embed with customers to learn their workflows, redesign and build production GenAI/LLM systems on AWS, ship and operate code, evaluate non-deterministic models, and own business outcomes.