Agile Lab

• Actively collaborate with business stakeholders to understand and translate functional requirements into technical specifications, ensuring proper implementation of use cases • Data flow implementation: design and implement new data flows on EDWH or Data Lake to meet specific business requirements, identifying and integrating necessary data sources • Data cleaning and preparation: conduct data preparation and cleaning activities to ensure the quality and reliability of the data used in analyses • Data quality techniques implementation: apply techniques and processes to ensure data integrity and reliability through quality control • Data model creation: develop specific data models for identified use cases, transforming input data into formats suitable for analysis and insight generation • Collaboration with dashboarding experts: work closely with dashboarding and data visualization experts to implement effective dashboards and reporting, presenting results in a clear and engaging manner

• Analyzes, designs, and implements complex systems • Challenges the team processes, looking for ways to improve • Mentors junior engineers via pairing, design, and code review • Builds software solutions by adhering to our quality standards about SDLC • Makes active efforts to stay up-to-date with technologies • Leads the technical design of complex systems • Understands and optimizes system performances • Takes the initiative to fix issues before they become a problem • Delivers complex systems, well-baked, and almost bug-free • Proactively identifies problems with requirements and project plan.

• Defining and driving the technical vision and strategy for Generative AI initiatives across projects and teams • Acting as a senior technical authority on GenAI system design, agentic architectures, observability, and production readiness • Advising multiple teams on architectural decisions, trade-offs, and best practices for ML and GenAI solutions • Overseeing the design and evolution of scalable, secure, and maintainable AI platforms • Leading and supporting pre-sales and client-facing activities: Conducting technical discovery and solution design; Assessing feasibility and analyzing risks; Contributing to proposals and delivering technical presentations • Managing stakeholders effectively in complex and ambiguous environments • Mentoring both senior and junior team members, fostering technical excellence and leadership development • Collaborating with leadership to evolve processes, standards, and organizational capabilities • Anticipating technological trends and identifying opportunities for innovation and continuous improvement

• Build and operate modern AI systems in production • Help build an AI Operating System: a harness‑centric runtime that turns powerful foundation models into reliable, long‑running systems • Provide structured capabilities—tool and filesystem access, code‑as‑action execution, skills loaded on demand, semantic grounding via knowledge graphs and ontologies, sub‑agent delegation, memory, and built‑in evaluation loops • Enable declarative agent design, where behavior emerges from clearly defined capabilities, constraints, and feedback • Model and leverage semantic layers across data and services: Knowledge graphs and entity relationships • Integrate semantic systems with retrieval and agentic workflows to support grounded answers, better contextualization, traceability • Build production-grade backend services and APIs that expose AI capabilities • Contribute hands-on to implementation, architecture, and engineering standards: Clean architecture, modular design, testing strategies • Evaluate new AI technologies quickly, understanding: when to adopt, when to wait, and how to mitigate risks • Collaborate with product, platform, and data teams to translate requirements into architecture decisions, delivery plans, measurable outcomes and quality gates • Produce high-quality technical documentation and architecture artifacts • Help teams and stakeholders navigate complexity with clear technical thinking and pragmatic choices • Make technical decisions under uncertainty and iterate safely, using experimentation and fast feedback loops, observability and measurable outcomes, fallback and rollback strategies

• Analyzes, designs, and implements complex systems • Challenges the team processes, looking for ways to improve • Mentors junior engineers via pairing, design, and code review • Builds software solutions by adhering to our quality standards about SDLC • Makes active efforts to stay up-to-date with technologies • Leads the technical design of complex systems • Understands and optimizes system performances • Takes the initiative to fix issues before they become a problem • Delivers complex systems, well-baked, and almost bug-free • Proactively Identifies problems with requirements and project plan • Go to an expert in one technological area • Research and propose new technologies • Detect possible performance bottlenecks • Known for drama-free launches • Can jump into an old project and fix it • Consistently influence technical and business roadmap of services/products/projects • Proactively identify and tackle tech debt • Communicate with self-awareness • When proposing something, at any level, is doing it in written form and providing the proper context • Contributes to the career development of others.

• Analyzes and implements a complex feature autonomously; • Builds software solutions by adhering to our quality standards about SDLC; • Participates in the technical design of features with guidance; • Understands and optimizes system performances; • Prioritizes tasks with autonomy based on requirements and proper context.

• Analyzes, designs, and implements complex systems • Challenges the team processes, looking for ways to improve • Mentors junior engineers via pairing, design, and code review • Builds software solutions by adhering to our quality standards about SDLC • Makes active efforts to stay up-to-date with technologies • Leads the technical design of complex systems • Understands and optimizes system performances • Takes the initiative to fix issues before they become a problem • Delivers complex systems, well-baked, and almost bug-free • Proactively Identifies problems with requirements and project plan.

• Maintain and administer the Cloudera CDP platform (Public or Private Cloud), ensuring availability, performance, and scalability • Monitor, scale, and manage Hadoop and Spark clusters, services (HDFS, Hive, Impala, HBase, Kafka, etc.), and associated infrastructure • Configure and manage security policies and data governance tools (Ranger, Atlas, etc.) • Develop automation scripts and pipelines for deploying and managing services across the data platform • Investigate and resolve platform and data pipeline issues, engaging with internal stakeholders and Cloudera support as needed • Continuously monitor system health, optimize resource usage, and improve performance of workloads and queries • Maintain clear documentation on procedures, configurations, incident responses, and best practices • Work with Data Engineers, Architects, and DevOps teams to integrate CDP into broader data pipelines and solutions • Participate in on-call rotation for critical incidents affecting platform operations

• Own new business development in France, with full responsibility for building pipeline and closing enterprise deals • Proactively open conversations with C-level and senior stakeholders (CDO, CIO, Heads of Data, Architecture) • Lead complex, multi-stakeholder sales cycles from first contact to closing • Work closely with Pre-Sales to shape solution narratives, demos, POCs and MVPs • Proactively engage prospects to clarify uncertainties, remove roadblocks and keep momentum high throughout the sales cycle • Position Witboost as a strategic platform, not a point solution • Build trusted relationships based on credibility, not feature selling • Collaborate with partners and resellers where relevant

• Prepare and deliver high-quality product presentations and demos, both onsite and remote • Help prospects understand how Witboost integrates with their existing ecosystem (data platforms, CI/CD, governance tools, catalogs, ticketing systems) • Support Sales in qualifying opportunities and shaping technically sound deal strategies • Define when a POC or MVP is the right next step and scope it clearly • Contribute to RFP/RFI responses and technical due diligence • Act as a bridge between customers and product, sharing feedback and field insights • Build reusable demo assets, solution patterns and reference architectures