AI Solution Architect

APGAR is a leading consultancy company specialized in Data Management and Artificial Intelligence
, helping organizations across industries harness the power of data and AI to drive strategic and operational transformation.

Your missions

As an AI Solution Architect, you will be part of a team working on Client projects. You will be supervised by a Technical Director or a Manager and will act as a technical reference for AI-related topics.

• You will work on all phases of AI and Data & AI solutions delivery, from use case definition to production readiness
• You will take part in the design and definition of AI solution architectures (data flows, AI services, integration, security)
• You will define the technical approach for AI solutions (ML, Generative AI, RAG, predictive models) and validate implementation choices
• You will define operating rules, non-functional requirements, and scalability principles for AI solutions
• You will supervise and validate the implementation carried out by technical teams or partners
• You will be responsible for continuous integration, deployment, and monitoring principles for AI solutions (MLOps supervision)
• You will endorse responsibility for the overall technical quality of AI solutions and support the project team on complex technical topics
• You will be accountable for the overall quality of deliveries and technical documentation (architecture documents, security notes, operating guides)
• You will assist the client in the setup, administration, and governance of AI solutions in cloud or on-premise environments, while defining methodologies and Dev Ops/MLOps processes
• You will be involved in effort estimation for tender calls
• You will write the technical and architectural sections of tender calls in full autonomy (writing and presentation)
• You will participate in client workshops and solution presentations to position AI solutions

• You will contribute to R&D activities in collaboration with the Offers and Innovation teams
• You will participate in the design of reusable AI architectures, frameworks, and accelerators
• You will take part in technical knowledge capitalization (best practices, reference architectures, AI patterns)
• You will evaluate new AI platforms, tools, and cloud services to enrich our AI offerings
• You will participate in internal initiatives (mentoring, offers structuring, community of practice, recruitment support)
• Depending on your career path wishes and desires, you will have the opportunity to move towards a position of technico-functional consultant. While still acting as a functional consultant, you will also be involved in the setting and configuration of the solution.

• Master’s degree or equivalent, with at least 5 – 8 years of experience in a consulting firm or IT services company
• You have designed, assessed, and guided the implementation of AI or advanced data solutions in enterprise environments
• You have strong experience in AI solution architecture and technical leadership
• You are comfortable working in client-facing and presales contexts
• You explained ML, GenAI, and Agentic AI concepts to non-technical stakeholders
• You communicated AI limitations, risks, and trade-offs clearly
• You have clearly written documentation and customer-facing summaries
• You participated in customer calls, demos, and workshops
• You did cross-functional communication with product, engineering, and sales teams

• Understanding of machine learning fundamentals (supervised/unsupervised learning, model training, evaluation)
• Familiarity with common ML algorithms (regression, classification, clustering)
• Basic understanding of feature engineering and data preprocessing
• Ability to interpret ML model outputs and performance metrics (accuracy, precision/recall, F1, etc.)
• Awareness of model overfitting, bias, and generalization
• Understanding of model lifecycle (training, validation, deployment, monitoring)

• Data architectures (data lake, lakehouse, batch & streaming)
• Data integration patterns, APIs, and enterprise systems
• Data quality, metadata, and governance concepts
• Strong…