Artificial Intelligence

• Learn and apply the security approach used in projects
• Analyze existing processes and tools: security requirements definition, project risk assessment, security assurance plan, security acceptance testing, and accreditation
• Identify control points for each project phase and how the process is implemented at a client organization
• Test the templates against real-world AI projects and document their limitations
• Design a project qualification framework covering use cases, data, in-house or third-party model, degree of autonomy, and exposure
• Develop a security requirements template combining CIA criteria and AI-specific criteria
• Build the associated security controls catalog: data and model protection, input and output filtering, agent guardrails, logging, human oversight, and reversibility
• Define acceptance criteria and corresponding security acceptance tests
• Test the toolkit on an internal project or client engagement and refine it
• Align the toolkit with AI security governance activities and accreditation processes
• Prepare materials for implementing the process at client organizations and train consultants

Internship – Security of Artificial Intelligence Projects and Associated Systems

• Drive the performance of a portfolio of engagements
• Anticipate risks and challenge financial trajectories
• Support the implementation of improvement plans
• Get involved from the pre-sales stage to challenge solutions and Delivery models
• Ensure commitments are fulfilled
• Support projects in sensitive situations
• Support and develop Engagement Managers through coaching, certifications, experience sharing, and skills development
• Accelerate industrialization, productivity, and the adoption of GenAI
• Contribute to the development and expansion of engagements

Delivery Head – Data & AI

• Lead the management and coordination of Delivery across the Data & AI France entity
• Ensure consistency across the various portfolios and bring together the Delivery Heads team
• Represent the Delivery priorities of the Data & AI entity to the Business Units and the Global Business Line Data & AI
• Oversee a portfolio of engagements to secure project delivery, improve performance, and contribute to customer satisfaction
• Lead and coordinate the team of four Delivery Heads
• Align priorities and operating models, promote the sharing of best practices, and facilitate decision-making and trade-offs
• Consolidate an overall view of engagement performance
• Identify risks, alerts, and opportunities; challenge improvement plans; and contribute to managing critical situations
• Promote predictability, financial control, and Delivery excellence
• Coordinate interfaces with the Business Units’ Operations Directors
• Represent Delivery priorities to the Global Business Line and support the rollout of global initiatives
• Lead continuous improvement, industrialization, productivity, and GenAI adoption
• Encourage the capitalization and sharing of practices and support the evolution of the Delivery model

Lead Delivery – Data & AI

• Support CIO organizations and business teams throughout the AI use-case lifecycle: scoping, tool selection, design, deployment, cost control, and adoption
• Gather pain points and opportunities, map processes, prioritize use cases, and formalize a roadmap with the CIO organization
• Assess and compare proprietary and open-source models, agentic platforms, orchestration tools such as n8n, and business copilots
• Build a functional, technical, security, and cost-based selection framework, then lead POCs
• Prototype use cases and orchestrate their integration with the existing information system, data, APIs, and business applications
• Support production deployment
• Build business cases, track usage costs, and measure ROI
• Define the target operating model and RACI roles across CIO organizations, business teams, and vendors
• Support change management and user adoption
• Ensure use-case compliance in collaboration with security stakeholders

Generative & Agentic AI Strategy and Transformation Consultant – F/H

• Support clients with their day-to-day technical needs and transformation initiatives
• Audit existing practices to identify high-value Data/AI use cases
• Design and implement Data and agentic pipelines
• Secure the outputs of AI models
• Manage scaling and cost challenges in Data/AI architectures
• Work with Google Cloud architectures and services, particularly Vertex AI
• Support the development of client teams’ skills through training and coaching
• Champion Zenika’s vision and new Data/AI offering
• Address a wide range of technical challenges as a well-rounded consultant
• Contribute to architecture modernization projects, product development initiatives, and long-term engagements
• Work in blended client/Zenika teams using Scrum or Kanban

Senior Consultant – Google Cloud, Data/AI

• Apply independent judgment to identify AI blind spots, reasoning failures, factual inaccuracies, contradictory evidence, and quality gaps
• Review and evaluate AI-generated responses in French
• Verify factual claims using reliable online sources and supporting evidence
• Assess whether evidence supports, contradicts, or fails to support AI-generated conclusions
• Evaluate response quality, relevance, completeness, and alignment with user intent
• Detect inconsistencies, unsupported claims, contradictory information, and missing evidence
• Challenge AI-generated conclusions when evidence suggests a different outcome
• Provide clear quality feedback and rationale for review decisions
• Participate in training, calibration, and quality alignment sessions conducted in English
• Maintain quality, consistency, commitment, and productivity expectations while meeting project requirements
• Collaborate with project teams to continuously improve reviewer standards and AI quality outcomes
• Complete guideline reviews, platform training, UI navigation exercises, knowledge assessments, fact-checking exercises, and project simulation tasks as part of qualification

AI Fact-Checking, Response Evaluation Reviewer – French

• Stay at the forefront of Generative AI and Agentic AI, including LLMs, multimodal models, tool-augmented agents and agentic workflows.
• Design, prototype, and rigorously evaluate specialized AI agents tailored to end-to-end insurance workflows.
• Translate business problems into robust agentic systems, including task decomposition, context and prompt design, tool integration, memory strategies, and advanced evaluation methodologies.
• Take ownership of AI systems from problem formulation and benchmarking to production deployment, monitoring, and continuous improvement.
• Contribute to internal frameworks, benchmarks, and shared tooling to accelerate experimentation and industrialization of agentic workflows.
• Collaborate closely with product, engineering, and data teams to ensure scalability and measurable business impact.
• Develop claim handling agents that automate tasks and processes, simplify claim handlers’ daily work, and enhance the insured’s experience.

Artificial Intelligence Researcher

• Understand the client’s context and productivity needs in order to define a realistic agentic TechOps platform tailored to their level of maturity
• Assess the current environment, identify quick wins, and prioritize use cases
• Define the methodology for documenting, designing, and evolving agents, as well as for creating runbooks and standardizing tools and scripts
• Build initial agents with teams for real-world TechOps and Cloud Operations use cases
• Connect agents to existing ticketing systems, monitoring tools, and cloud platforms, with access rights defined according to the principle of least privilege
• Measure value through real-world use cases, track key metrics, and progressively expand the scope of the agents
• Determine whether to use an agent, a script, or an improved procedure
• Onboard teams to an AI-first approach and enable them to operate independently
• Depending on experience, frame use cases with decision-makers and present a quantified value proposition

Consultant, TechOps & AI

• Identify and map HSE processes and activities that could benefit from Artificial Intelligence, focusing on high-value use cases
• Design and test Generative AI solutions for HSE activities, including document drafting, field data analysis, audits and inspections, reporting, document management and regulatory monitoring
• Develop AI user guidelines and best practices
• Support HSE teams in adopting new digital tools through change management initiatives and pilot projects
• Analyze existing HSE indicators and reporting needs to define a structured performance monitoring framework
• Develop and automate dashboards using Power BI, Excel or other Business Intelligence tools
• Improve data collection and consolidation
• Monitor HSE performance and prevention indicators, including workplace accidents, near misses, safety audits, corrective actions, regulatory training and compliance
• Produce data-driven analyses to support action plans and management decision-making
• Contribute to the HSE Department’s AI roadmap, automated reporting system and continuous-improvement recommendations

Internship – AI & HSE Performance Analyst

• Scope and advise clients on their AI use cases, aligned with their business objectives and Microsoft strategy
• Lead workshops with business and IT teams, challenge ideas, and identify relevant solutions
• Translate business needs into concrete, feasible AI functional solutions
• Advise business leadership and IT departments on Microsoft Copilot, Copilot Studio, and agentic AI
• Identify prerequisites for deploying AI agents, including data, governance, security, compliance, architecture, and change management
• Contribute to defining AI roadmaps and adoption strategies
• Design and develop AI agents with Microsoft Copilot Studio
• Configure topics, actions, tools, instructions, and orchestration mechanisms
• Use Power Automate to automate business processes and orchestrate agent actions
• Connect agents to Microsoft 365, including SharePoint, Teams, and Dataverse
• Integrate agents with business applications and external services through connectors and APIs
• Participate in POCs, prototyping, testing, and iterations through to production deployment
• Implement grounding, testing, guardrails, evaluation, and conversation monitoring
• Analyze agent performance and contribute to continuous improvement
• Participate in demonstrations, hands-on workshops, training sessions, and hackathons
• Contribute to the industrialization, deployment, ALM, and lifecycle management of AI agents
• Contribute to structuring Power Platform environments and deployment strategies
• Participate in testing, user acceptance testing, production deployment, and solution stabilization
• Ensure the quality, security, governance, and maintainability of solutions
• Document architectures, configurations, processes, and solutions
• Raise client awareness of governance, compliance, security, and Responsible AI
• Maintain technology watch on Copilot Studio, agentic AI, Microsoft 365 Copilot, Power Platform, and Azure AI
• Explore new features and their potential for client projects
• Share lessons learned and best practices with teams
• Contribute to the development of AI methodologies, frameworks, accelerators, and offerings
• Participate in pre-sales activities, tender responses, and the scoping of AI projects
• Support consultants’ skills development and knowledge sharing within the AI community

Artificial Intelligence jobs in France