Senior Forward Deployed Engineer / Senior Solutions Architect

Enterprises are adopting AI faster than they can govern it — and they are looking for a partner who can do two things at once: speak credibly about AI trust, governance, and security, and actually build. The Forward Deployed Engineer (AI) is that partner. You are the technical face of AvePoint inside client organizations: equally comfortable whiteboarding AI trust and governance concepts with a CISO, translating a business problem into a scoped AI build project, and writing the first working prototype yourself. You embed with clients, ship real outcomes, and own the engagement end to end. This is not a pre-sales role with a demo script, and not a back-office delivery role. It is the engagement model pioneered by leading AI companies for their strategic enterprise customers: a senior engineer deployed forward, with the autonomy to own the problem from first workshop to production. WHAT YOU'LL DO ADVISE ON AI TRUST AND GOVERNANCE. Lead workshops that help clients understand and take control of their AI landscape — agents, copilots, models, and the data behind them, including the shadow AI they didn't know about. Explain AI governance, security posture, and resilience concepts credibly to both technical teams and executives. Guide clients through obligations such as the EU AI Act, NIS2, and ISO 42001, and help them stand up practical operating models: AI inventories, approval workflows, risk classification, and audit evidence. SCOPE AND SHAPE AI BUILD PROJECTS. Sit with business stakeholders to understand the underlying need behind "we want AI for X." Identify the highest-value use cases, define success criteria, and translate ambiguous requirements into concrete, estimable technical scopes — architecture outlines, data and integration requirements, delivery phases, effort and risk assessments. Write statements of work that engineering teams can actually deliver and clients can actually sign. BUILD AND DELIVER. Develop prototypes and production components for client AI solutions: agent workflows, RAG pipelines, LLM integrations (Azure OpenAI, AWS Bedrock, Google Vertex, Anthropic), MCP-based tool integrations, and the governance and security controls around them. Deliver custom adapters and local tooling for regulated, cloud-restricted, or air-gapped environments where standard SaaS approaches cannot go. OWN THE RELATIONSHIP THROUGH DELIVERY. Act as the trusted technical advisor from first workshop through go-live: run enablement sessions, support adoption, troubleshoot in production, and expand the engagement where you see genuine value for the client. WHAT WE'RE LOOKING FOR MUST-HAVES * 5+ years in software engineering, solutions architecture, or technical consulting, with at least 2 years hands-on with modern AI/LLM systems in real projects (not only experimentation). * Practical experience building with LLM APIs and frameworks (e.g., Azure OpenAI, Bedrock, Vertex, LangChain, Semantic Kernel) and patterns such as RAG, agentic workflows, and tool/function calling. * Machine Learning Expertise: Hands-on machine learning experience spanning model development, evaluation, deployment, and operationalization, with a focus on enterprise AI solutions, predictive analytics, and scalable MLOps practices. * Strong programming skills in Python and/or C#/TypeScript, plus working fluency with at least one major cloud platform (Azure, AWS, or GCP), including identity, networking, and data services. * Demonstrated ability to scope technical projects from ambiguous business requirements: you can run a requirements workshop, challenge assumptions constructively, and produce a credible plan with phases, estimates, and risks. * Excellent communication in front of senior stakeholders — you can explain why AI governance matters to a board member and debate vector database trade-offs with a platform engineer in the same meeting. * Willingness to travel to client sites and to operate with high autonomy in ambiguous, fast-moving engagements. STRONG PLUSES * Working knowledge of AI governance and compliance frameworks: EU AI Act, NIS2, ISO/IEC 42001, NIST AI RMF, or Gartner's AI TRiSM model. * Experience with AI security topics: prompt injection, data leakage, agent permissioning, model and data security posture (AI-SPM/DSPM concepts). * Familiarity with the Model Context Protocol (MCP), agent runtimes, or vector databases (e.g., Pinecone, Milvus, Weaviate, Chroma). * Background in enterprise data governance, security, backup/resilience, or the Microsoft 365 / multi-cloud ecosystem where AvePoint operates. * Experience delivering into regulated industries (public sector, defense, financial services, healthcare) or air-gapped/sovereign environments. * Prior experience in a forward-deployed, embedded consulting, or customer-facing engineering role. * Additional languages relevant to your region's client base. HOW WE'LL MEASURE SUCCESS Within your first 6–12 months, you will have led AI discovery and governance workshops for multiple enterprise clients, scoped and won at least one significant AI build or governance engagement, and delivered working software into a client environment. Above all: clients ask for you by name. WHY THIS ROLE, WHY NOW AI adoption has outrun enterprise control, and regulators have noticed. Every large organization now needs to see, govern, secure, and sustain its AI estate — and most need a partner who can both advise and build. As an FDE at AvePoint you will help define this engagement model from the ground floor, work at the frontier of agentic AI and AI trust, and do it with two decades of enterprise data governance and resilience expertise behind you.   #LI-SB1 Any personal data you share with us during the application process will be processed strictly in compliance with applicable data protection laws and our Privacy Notice [https://www.avepoint.com/company/privacy-notice].

ABOUT PARLOA Parloa’s mission is to make every customer conversation feel effortless for both customers and the companies serving them. As agentic AI accelerates, Parloans are shaping the foundation of a new era in customer experience, one where customer support is no longer transactions, but meaningful exchanges. It is not just a vision; Parloa has powered over ONE BILLION interactions between global enterprise brands and their customers, with companies like Booking.com, HealthEquity, Allianz, SAP, BarmeniaGothaer, and TUI already deploying Parloa at scale. ABOUT THE ROLE: As a Senior Forward Deployed Engineer at Parloa, you’ll be on the front lines of enterprise AI adoption — delivering cutting-edge technology into some of the most complex environments in the world. This is your opportunity to lead end-to-end deployment projects from an engineering perspective — not just implementing what exists, but engineering what’s required to make it succeed at enterprise scale. FDEs are our in-field product engineers. You will build what doesn’t yet exist, adapt architecture to enterprise realities, and engineer integrations across systems and APIs to make deployments successful. Your work is hands-on and code-first — you’ll be building, debugging, and engineering solutions directly in the field. What you ship not only makes deployments succeed, it also defines how customers experience Parloa and shapes what our product becomes. This is not about maintenance. This is about engineering what makes it work in production, under real-world enterprise constraints, at speed and scale. AREAS OF OWNERSHIP: * Own deployment engineering projects: Lead the technical execution (incl. product engineering) of Parloa’s deployments inside large, complex enterprise environments * Design for scale and resilience: Architect deployment solutions that meet enterprise-grade requirements for performance, reliability, and security * Engineer solutions where none exist: Build custom extensions, integrations, and configurations to close product gaps and meet enterprise requirements * Work across systems & stacks: Operate at the intersection of backend engineering, DevOps, and data engineering to ensure seamless delivery * Partner with enterprise teams: Collaborate directly with customer engineering organizations to overcome constraints and deliver measurable outcomes * Guide and mentor others: Collaborate with and provide technical guidance to more junior in-field engineers * Influence at senior levels: Engage with enterprise architects and senior technical stakeholders, discussing solutions and architectures in depth to ensure alignment and credibility * Debug under pressure: Rapidly unblock issues in mission-critical environments and ensure customer success. * Shape the product: Act as the feedback loop between the field and our core engineering teams — turning deployment learnings into platform evolution * Deliver long-term impact: Work closely with Deployment Strategists to ensure scalable architectures and durable customer value OUR TECH STACK:  Typescript, NodeJS, OpenAI, Microsoft Azure, Kubernetes, Docker, Terraform, MongoDB, MySQL, Redis, Kafka, MCP WHO YOU ARE: * 7+ years of professional experience in software engineering, systems integration, DevOps, or data engineering roles with direct customer impact * Proven track record of leading deep technical deployments and integrations in large-scale enterprise environments * Strong technical depth across backend engineering, infrastructure-as-code, Kubernetes/cloud platforms, APIs, and databases - with proven experience in systems design and the ability to go hands-on in production systems * Ability to operate independently in ambiguous, high-responsibility settings, especially when deploying live to enterprise systems * A builder’s mindset with bias for action, creativity under pressure, and an obsession with making things work in the real world * Degree in Computer Science, Engineering, or related technical field * Native or near-native French language skills and professional fluency in English * Strong plus: Experience building or integrating AI/LLM-powered systems (e.g., embedding agent workflows, vector databases, prompt orchestration) OUR RECRUITING PROCESS: Talent Acquisition → Hiring Manager → Technical Interview(s) → Bar Raiser WHY PARLOA? We’re at the beginning of a new era in customer experience, one where AI doesn’t just respond, but understands, reasons, and takes action. We’re building agentic AI that enterprises trust with their most important customer moments: complex questions, high volumes, real stakes. When millions of people reach out to a brand, those interactions aren’t just support tickets; they’re defining experiences. We’re here to raise the standard: making every conversation seamless, intelligent, and genuinely helpful. If you care about shaping how businesses and customers connect at scale and want your work to matter in real, everyday moments, this is where you do it. At Parloa, ownership isn’t a buzzword; it means being accountable for outcomes, not just tasks. We operate in a category that’s evolving fast, where the bar is high, and the problems are complex. We hire people who think in solutions, communicate with clarity, and follow through. People who are comfortable making decisions, taking responsibility, and raising the standard for themselves and those around them. We’ve grown beyond the earliest startup phase, but we’ve kept the intensity: fast execution, direct feedback, and a strong expectation to contribute meaningfully from day one. Backed by leading global investors like General Catalyst, EQT Ventures, and Altimeter Capital, we’re scaling with a clear ambition: to become the global category leader in enterprise-grade conversational AI.   ---------------------------------------------------------------------------------------------------------------------------------- Parloa is committed to upholding the highest data protection standards for our clients' and employees' data. All our employees are instrumental in ensuring the utmost care, GDPR, and ISO compliance, including ISO 27001, in handling sensitive information. Parloa is an e-verify employer in the USA. Please click here to learn more. * We provide equal opportunities to all qualified applicants regardless race, gender, sexual orientation, age, religion, national origin, disability status, socioeconomic background and other characteristics.