Artificial Intelligence

• Identify and approach potential B2B clients across the European Union.
• Build and manage a sales pipeline independently.
• Present DPO-One’s SaaS solution to companies dealing with GDPR, data privacy, and AI Act compliance challenges.
• Engage with stakeholders and decision-makers to create interest and management buy-in.
• Conduct product introductions, presentations, and demos when needed.
• Understand client needs and position the solution in a consultative way.
• Support the development of the go-to-market strategy for GDPR and AI Act compliance use cases.
• Work closely with leadership to refine sales messaging and market approach.

Sales Manager – GDPR, AI Act Compliance SaaS

• Accompany clients in identifying where AI and data can create the most value, scope the right initiatives, and make sure the solutions delivered fit their strategic stakes.
• Act as a trusted advisor on AI transformation, an AI coach for business teams, and a hands-on contributor when needed.
• Work closely with client stakeholders and internal team members to:
• Frame business questions into clear AI and analytics opportunities
• Run discovery and needs-scoping sessions with both business and technical stakeholders
• Translate between business language and technical reality, in both directions
• Identify the right KPIs and the right type of solution for each stake (analysis, model, dashboard, automation, agent, AI workflow)
• Coach business teams on how to use AI tools and AI products responsibly in their day to day
• Structure roadmaps and priorities with clients, from quick wins to longer-term plays
• Build prototypes, dashboards, models, or automations to demonstrate value where relevant
• Communicate findings, trade-offs, and recommendations to both technical and executive audiences
• Support implementation and adoption so that work leads to concrete action
• Complete assignments typically include AI audits, AI roadmaps, use case scoping, hands-on AI delivery, coaching of business teams on AI ways of working, and the more traditional data analytics work that often comes alongside.
• Supervise and coach junior team members on client missions and internal initiatives, helping them grow on the business, consulting, and technical sides of the job.

Senior Consultant, AI & Strategy

• Lead projects end to end, from proposal to delivery, across data science and AI use cases.
• Own client relationships and grow them over time, with real accountability for outcomes.
• Spot commercial, technical, and organizational opportunities, and turn them into action without waiting for permission.
• Coach consultants on technical skills, project management, and client interaction.
• Help shaping the direction of the AI & Strategy practice: what we offer, how we work, where we go.
• Drive internal initiatives that improve how Agilytic operates.

Manager, AI – Strategy

• Act as the primary point of contact for clients and partners during AI implementation initiatives, ensuring clear communication, expectation alignment, and structured execution.
• Guide clients in translating business requirements into AI deployment strategies leveraging QVAC capabilities (local inference, delegated compute, privacy-preserving architectures).
• Support Expansion team in shaping AI-related opportunities by providing input on feasibility, integration complexity, and delivery approach.
• Identify opportunities to extend implementations across additional use cases, geographies, or Tether technologies.
• Lead end-to-end coordination of QVAC-based implementations from kickoff through production deployment.
• Define implementation roadmaps, milestones, and dependencies across AI models, infrastructure, and integration layers.
• Ensure alignment between client expectations and actual product capabilities, avoiding scope drift or mispositioning.
• Track progress across multiple concurrent AI deployments, ensuring timely delivery and readiness for production environments.
• Coordinate closely with product, engineering, and research teams to align on QVAC capabilities, limitations, and roadmap evolution.
• Facilitate integration between client systems and QVAC components, including model deployment pipelines, APIs, and compute environments.
• Work with legal and compliance teams where required, particularly in sensitive AI deployments involving data locality or privacy constraints.
• Maintain structured communication flows across all stakeholders involved in the implementation lifecycle.
• Establish and maintain governance frameworks including implementation plans, risk tracking, and decision logs.
• Produce executive-level updates summarizing progress, risks, blockers, and next steps.
• Ensure documentation of implementation architectures, deployment patterns, and key learnings for reuse across future projects.
• Support escalation management and ensure timely resolution of technical or operational challenges.

Engagement Manager – AI Implementations

• Build the integration layer
• Design and build a Python microservice that acts as the integration layer between Oper's product and the customer's banking systems
• Define clean API contracts (REST, OpenAPI) on both sides of the integration
• Implement reliable request handling, retries, idempotency, and error semantics across system boundaries
• Translate between Oper's domain model and the customer's data formats and protocols
• Treat the integration as a real product: versioned, documented, and easy to evolve
• Ship a production-ready service
• Build the service with FastAPI, async patterns, and strong typing
• Set up observability end to end: structured logging, tracing, metrics, alerts
• Handle authentication, secrets, and sensitive data correctly from day one
• Containerize and deploy via our existing CI/CD setup
• Write meaningful tests at the right level (unit, integration, contract)
• Use modern AI coding tooling (Cursor, Claude Code, Copilot, or your own setup) as a core part of how you build, not as an afterthought
• Apply AI to the parts of the work where it actually compounds: scaffolding, adapters from spec, generating tests, reviewing diffs, writing documentation
• Be honest about where AI helps and where it does not, and design your workflow accordingly
• Aim for a delivery cadence and output level that a non-AI-native engineer simply cannot match
• Collaborate and communicate
• Own the delivery rhythm: weekly demos, written updates, clear progress signals
• Ask the right clarifying questions early and proactively flag risk
• Work closely with the Oper engineering, product, and customer-facing teams
• Leave behind code, documentation, and runbooks that the internal team can confidently maintain after the engagement

AI-Native Engineer – Freelance

• Drive AI literacy and usage across all teams (Product, Engineering, Sales, Finance, HR, etc.)
• Ensure AI becomes part of day-to-day workflows, not isolated experiments
• Define and promote best practices for responsible and effective AI usage
• Contribute to building a strong internal AI culture (events, rituals, communication)
• Lead and coordinate the Rydoo AI Guild
• Structure Guild initiatives, priorities, and outputs
• Ensure continuity despite member rotation
• Facilitate collaboration across functions and ensure balanced representation
• Identify high-impact AI use cases across the organization
• Help teams prioritize and execute these use cases
• Support teams in moving from ideas to real, measurable outcomes
• Ensure learnings are shared and scaled across the company
• Help evaluate and guide the selection of AI tools (company-wide and team-specific)
• Ensure coherence in tooling choices across the organization
• Support onboarding and effective usage of selected tools (e.g. Claude or others)
• Promote safe and compliant use of AI tools (data privacy, security, policies)
• Work with IT/Security and Legal when needed
• Help define guardrails without slowing down adoption
• Define KPIs to track AI adoption and impact (productivity, quality, speed)
• Monitor progress across teams
• Ensure AI initiatives translate into tangible business outcomes

AI Transformation Lead

• Achieve pipeline generation and revenue targets for allocated accounts
• Execute tailored sales plays to capture market opportunities in AI/ML
• Work directly with customers to understand their AI/ML needs
• Become an expert in Snowflake’s AI/ML solutions
• Work with Account Executives and Sales Engineers to drive customer engagements
• Track, analyze, and report on AI/ML sales performance metrics
• Partner with cross-functional organization to integrate AI/ML sales efforts

AI Product Sales Specialist

• Translate the Product Roadmap into clear business requirements, user stories, and functional specs.
• Act as the bridge between business and AI/tech teams, ensuring alignment and smooth delivery.
• Document and optimize process flows, workflows, and functional specifications, identifying opportunities for automation and AI integration.
• Improve business processes by spotting inefficiencies and proposing AI-powered solutions (chatbots, digital assistants, intelligent agents).
• Work closely with stakeholders to align priorities, manage expectations, and track progress.
• Support testing, rollout, and adoption of new digital and AI-enabled solutions.
• Provide insights and reporting on performance, KPIs, and adoption metrics to guide decision-making.
• Demonstrate a proactive commitment to transition into a management or leadership role as the team and portfolio expand.

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