Jobs at Skan AI

Administer PostgreSQL databases, including monitoring, maintenance, backup and recovery, performance tuning, replication, high availability, and disaster recovery. Troubleshoot database and operational issues independently, manage security and access controls, and support PostgreSQL deployments and migrations in Kubernetes using CloudNativePG. Perform basic MongoDB administration, monitoring, and optimization while collaborating with DevOps and platform teams on production support and incident resolution.

Own the technical sales process for enterprise agentic AI deals, from qualification through signature. Scope proofs of concept, define success criteria, design cloud, hybrid, customer-hosted, and on-premises deployments, and lead architecture and security reviews. Develop commercial proposals, statements of work, infrastructure requirements, and order form exhibits while creating reusable sales assets. The role serves regulated enterprises and requires expertise in sales engineering, solutions architecture, vendor risk reviews, and complex enterprise deal cycles.

Own customer-facing agentic AI deployments from kickoff through initial deployment. Coordinate engineering and solutions teams, manage stage gates, dependencies, risks, timelines, and deliverables, while keeping executive sponsors informed. Develop standardized deployment playbooks, reporting, runbooks, and engagement processes that scale across customers. The role combines technical program coordination, stakeholder management, documentation, and delivery leadership in a fast-changing startup environment.

Owns the administration, optimization, scalability, monitoring, reliability, and architecture of PostgreSQL, MongoDB, and Databricks environments. Responsibilities include performance tuning, schema configuration, observability, autoscaling, capacity planning, production troubleshooting, maintenance, high availability, disaster recovery, incident response, and data analysis support. The role designs resilient, cost-efficient data platforms at very high volumes and partners with engineering, analytics, and product teams.

Develop scalable AI and machine learning systems that infer business processes, decision logic, variations, and exceptions from event logs, documents, screen recordings, and UI traces. Build process representations, retrieval and grounding systems, evaluation frameworks, and reliability tooling for downstream agentic execution. Apply algorithms, graph methods, structured prediction, representation learning, foundation-model adaptation, and multimodal techniques while translating research into production systems.

Lead research and production development of scalable AI systems that infer business-process structure from event logs, UI traces, recordings, and documents. Develop process discovery, representation learning, retrieval, evaluation, grounding, and foundation-model adaptation methods. Establish reliability standards, diagnose production failures, guide architecture, collaborate across research and engineering, and mentor scientists and engineers. The role emphasizes algorithmic thinking, multimodal and language-model systems, process mining, rigorous evaluation, and translating research into reliable agentic AI products.

Productionize research and agentic AI systems into reliable, scalable backend services. Design Python microservices, asynchronous distributed pipelines, workflow orchestration, data layers, testing frameworks, CI/CD, and infrastructure across cloud, hybrid-cloud, and on-premise environments. Own observability, performance, deployment, regression prevention, production support, and on-call operations while collaborating with research, AI, product, and platform teams.

Own strategic enterprise accounts, overseeing delivery, governance, executive relationships, customer satisfaction, retention, and expansion. Use process intelligence and value frameworks to identify transformation opportunities, measure ROI, build business cases, and connect Skan’s platform to customers’ AI roadmaps. Lead QBRs, resolve escalations, support demonstrations and discovery, coach CSMs, and collaborate with Sales, Engineering, Product, and delivery teams.

Build and own production machine learning models and large-scale data pipelines for process intelligence applications. Responsibilities include feature engineering, experimentation, deep learning, NLP, data quality monitoring, production issue diagnosis, and customer data troubleshooting. The role also mentors junior data scientists, conducts code reviews, develops diagnostic tooling, and collaborates with product, engineering, and customer-facing teams.

Lead the vision, strategy, roadmap, and execution of Skan AI’s enterprise process intelligence platform. Manage product delivery across process discovery, analytics, conformance, and integrations while partnering with engineering, design, data science, sales, and customers. Build and develop the product management team, establish operating processes, guide AI-assisted product work, shape commercial positioning, and represent the product in executive customer engagements.

Designs and executes 1:1 account-based marketing programs for enterprise customer expansion. Builds account plans, coordinates sales and marketing teams, develops personalized multi-channel campaigns, manages budget, tracks engagement and pipeline, reports performance, and contributes insights to the broader ABM playbook.

Own Skan AI’s SEO and AI search strategy across Google, ChatGPT, Claude, and other platforms. Drive organic visibility, citations, qualified traffic, and pipeline through technical SEO, content optimization, structured data, entity SEO, analytics, and scalable workflows. Partner with marketing teams, manage tools and budgets, monitor performance dashboards, and present actionable insights to leadership.

Build and own production machine learning models and data pipelines for process intelligence, including task detection, workflow segmentation, behavioral analysis, and process discovery. Responsibilities include feature engineering, model evaluation, experimentation, large-scale multimodal data processing, data quality monitoring, production issue diagnosis, and cross-functional communication with engineering, product, customer success, and solutions teams.

Lead and build Skan AI’s L2 technical escalation function. Manage senior engineers, establish escalation and incident processes, troubleshoot complex issues across data, networking, APIs, LLM applications, databases, and platform performance, and partner with Product Engineering on resolutions. Drive root-cause analysis, preventive improvements, documentation, knowledge management, customer communication, and operational metrics.

Owns end-to-end deployment, configuration, maintenance, upgrades, monitoring, and troubleshooting of customer-hosted enterprise software environments. Designs infrastructure architectures, validates readiness, manages incidents and disaster recovery, documents customer environments, and partners with customer IT, DevOps, and onboarding teams. The role also provides technical customer engagement across deployment, support, optimization, and incident response, including on-call participation and root cause analysis.

Lead Skan AI's content function end-to-end: define narrative and editorial voice, build AI-powered content operations, drive thought leadership, SEO, demand-gen/ABM alignment, sales enablement, and performance analytics while managing a cross-functional team and external agencies.

Lead product marketing to define positioning, messaging, GTM strategy, and analyst relations for an enterprise AI/process-intelligence B2B SaaS platform. Build product marketing infrastructure, enable sales, drive launches, customer advocacy, and inform product roadmap through market research and competitive intelligence. Hire and scale the function and present to executive leadership and board.

Own the technical sales process for enterprise AI automation deals, from qualification and proof-of-concept scoping through architecture, security review, pricing, and contract execution. Design deployments across cloud, hybrid, customer-hosted, and on-premises environments while addressing data residency and recording restrictions. Partner with account executives on business cases and commercial proposals, write statements of work and infrastructure requirements, and develop reusable sales assets. The role serves large regulated enterprises with complex, multi-stakeholder sales cycles.

Owns end-to-end technical architecture for strategic customer deployments, including enterprise technology discovery, gap analysis, integration design, deployment model selection, HA/DR planning, and cloud connectivity. Presents solutions to CTOs and IT leaders, coordinates DevOps, Security, onboarding, and client teams, and oversees architecture approval through go-live. Develops reusable reference architectures and ensures deployments are integration-ready, secure, and operationally sound.

Owns inbound and outbound pipeline generation, including targets, account strategy, messaging, qualification, forecasting, and reporting. Builds and manages the BDR team through hiring, onboarding, ramp certification, coaching, performance management, and career development. Partners with sales, marketing, partnerships, enablement, and revenue operations to improve pipeline quality and coverage. The role also directly prospects into strategic enterprise accounts and develops scalable processes for B2B SaaS sales development.