Jobs at Axiamatic, Inc.

Build and shape an agent-orchestration platform using frontier LLMs. Transform heterogeneous enterprise program data into structured, queryable knowledge, develop reliable and observable backend services, and own features from design through production. Collaborate with product management and customers, make prioritization decisions, review code, write tests, and support production systems. The role requires strong Python backend skills, LLM production experience, cloud expertise, and comfort solving ambiguous startup problems.

Leads a forward-deployed engineering team delivering customer-specific software and AI solutions for complex ERP and IT transformations. Partners with enterprise stakeholders on discovery, architecture, pilots, integrations, and production deployments. Builds AI agents, analytical workflows, data pipelines, and enterprise applications while establishing secure, scalable engineering practices. Identifies reusable patterns across engagements and converts successful solutions into product capabilities. Mentors engineers, influences product strategy, and develops repeatable deployment approaches for enterprise customers.

Owns end-to-end implementation and onboarding for Axiamatic’s agentic platform, translating customer goals into configured solutions and driving rapid first value. Manages roadmaps, scope, timelines, customer commitments, and Forward Deployed Engineers. Leads adoption, quarterly business reviews, value realization, expansion identification, and churn-risk mitigation while engaging executive stakeholders. Requires Big Four transformation consulting experience, multiple ERP implementations, strong project management, customer value delivery, and the ability to explain agentic AI capabilities to nontechnical audiences.

Lead the technical side of SAP sales cycles by conducting discovery, delivering tailored demos, designing solution architectures, addressing technical objections, and managing proofs of concept through technical decisions. Partner with SAP architects, IT leaders, executives, product teams, and forward-deployed engineers across S/4HANA, ECC, BTP, RISE, and Clean Core environments.

Own a major enterprise transformation platform area end to end, including strategy, roadmap, execution, enablement, customer discovery, and metrics. Drive products from concept through launch while improving production offerings. Partner closely with engineering on prioritization, specifications, and technical tradeoffs; shape AI agents, context graphs, and playbooks for transformation stakeholders. Represent the company with customers, partners, and the market through briefings, events, and written content.

Own a major enterprise transformation product area end-to-end, including strategy, roadmap, execution, enablement, metrics, and customer outcomes. Drive both 0-to-1 launches and scaling of production products, partner closely with engineering and design, define AI agent experiences, translate customer needs into specifications, and represent the company with customers, partners, and the broader market.

Generate outbound and inbound pipeline through email, phone, and LinkedIn prospecting; build account targeting, messaging, and sequencing from scratch; qualify leads and hand them to account executives; support discovery calls with research and account mapping; evaluate prospecting tools; document repeatable sales plays; and provide market feedback on AI infrastructure buyers, objections, and competition.

Own customer-facing product management for enterprise ERP and IT transformation programs. Engage stakeholders to identify risks, dependencies, and inefficiencies; build analytical artifacts and AI-driven analysis specifications; translate customer insights into scalable product capabilities; support pre-sales, pilots, and proof-of-concept engagements; and inform the product roadmap through customer feedback.

Own forecasting, pipeline analytics, revenue dashboards, GTM technology, data infrastructure, and reporting. Build the company’s AI agent foundation by identifying automation opportunities and deploying production-grade agents across the sales organization. Partner with Sales Operations to maintain data integrity, define pipeline logic, and support forecasting. Design quota models and administer compensation plans while building and leading the Revenue Operations team in an early-stage B2B software environment.

Build and support scalable backend applications and enterprise software using Python, REST APIs, microservices, relational databases, cloud platforms, and modern deployment practices. Design reliable, observable, performant, and cost-efficient systems; collaborate with product management and distributed teams; contribute to technical decisions; and support production services. Experience with LLMs, generative AI, retrieval-augmented generation, vector databases, AI agents, Kubernetes, infrastructure as code, and observability is preferred.