Deployment Strategist

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. 

We are on a mission to transform how people interact with companies by making every conversation seamless, personalized, and human-like. Our AI Agent Management Platform empowers enterprises to create and manage AI voice and chat agents at scale, turning interactions into lasting relationships.

As our Deployment Strategist, you will drive AI transformation at Global 2000 enterprises as the “Field CPO” for Parloa’s most strategic customers. You will own the bridge between customer outcomes and product reality, translating business needs into deployable product capabilities for customers like Booking.com, Allianz, Decathlon, and TUI.

This is an opportunity to build a new industry. Agentic AI for enterprise is nascent. You’ll define what “good” looks like - at the forefront, with the hardest customers, solving the toughest problems.

• Land big clients (Global 2000 with complex, off-roadmap needs) and ensure their AI transformation succeeds.
• Manage stakeholders across business and tech (CEO, COO, CIO, CTO, VP Support), owning deployment from value thesis through production to expansion.
• Translate customer needs into product capabilities (not one-off customizations) that become reusable platform features.
• Build prototypes, make product changes, and create business plans hands-on - execution over PowerPoints.
• Represent customers to Parloa Product and represent Parloa Product to customers, bridging both worlds.
• Navigate ambiguity in agentic AI workflows, ROI models, and change management where no playbook exists yet.
• Own hard conversations: tradeoffs, “no,” re-scoping, and timeline realism with strategic accounts.
• Influence without authority across Product, Engineering, Sales, and Customer Success to drive outcomes.
• Feed validated learnings to product roadmap, turning customer work into platform capabilities that compound.

• 7-12 years of experience in enterprise software (solution architecture, product, or consulting) with a proven track record of customer-facing delivery.
• “Field CPO” mentality: ability to translate customer outcomes into product reality and vice versa.
• Business + tech stakeholder leadership: presented to C-suite across business and tech functions, demonstrated value, and ensured solutions make business sense.
• Product thinking: built client-specific roadmaps aligned with platform strategy.
• Architectural credibility: scoped off-platform features, assessed feasibility, and ensured supportability.
• Influence without authority: led cross-functional teams (Product, Eng, Sales, CS) without direct reports.
• Adaptability: comfortable being uncomfortable, willing to learn, operates in ambiguity.
• Hands-on execution: gets hands dirty - built prototypes, made product changes directly, created business plans. Not just an advisor.

• Industry diversity: experience in travel, fintech, insurance, retail, healthcare, telecom, or enterprise software - we’re building a team with a broad industry perspective.
• Industry-changing companies: worked at companies that transformed their industry (Booking.com, Decathlon, N26, Deel, Stripe, Uber, Airbnb).
• Hypergrowth experience: thrived in fast-scaling environments (e.g., 25 to 1500 people).
• Background as Palantir Deployment Strategist, AWS/GCP Solutions Architect, or product roles at hypergrowth tech.
• Tech stack: architectural understanding of Python, TypeScript, Terraform, K8s, Azure/AWS.
• AI/ML: LLM pipelines, agentic AI deployment, prompt engineering.
• Learning loop: created reusable patterns from custom work, fed learnings to product.

TA Screen (45 min) → Hiring Manager Call (45 min) → Product + Commercial Stakeholder Call (60 min.) →Technical Stakeholder Call (60 min.) → Case Study (take-home) → Bar Raiser Interview (60 min.)