Agentic AI Solution Architect (Revenue Management)

ITC Infotech; Paris; On-site; EUR 120,000 - 180,000; Full time

Job summary

ITC Infotech in Paris is seeking a Forward Deployed Engineer & Agentic AI Solution Architect to lead the design, development, and deployment of Agentic AI solutions in hospitality and Revenue Management. You will drive engagements from opportunity assessment to production deployment with hands-on engineering leadership.

This senior role blends business consulting, solution architecture, and technical execution, requiring strong strategic thinking and practical engineering capabilities across

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, Information Systems, or a related field.
• 10+ years of experience in software engineering, data engineering, AI/ML, enterprise architecture, or solution engineering.
• Hands-on experience designing and implementing Agentic AI and Generative AI solutions.

Responsibilities

• Lead end-to-end architecture for Agentic AI solutions, including multi-agent design and orchestration, tool and API integrations, retrieval-augmented generation, memory and contextual reasoning, guardrails and governance, and observability.
• Drive solutions from concept to production deployment and value realization, providing technical leadership to teams and partners.
• Review designs, code, and deployments to ensure quality, scalability, and alignment with business objectives.

Skills

Python

SQL

REST APIs

Enterprise integrations

Event-driven architectures

Identity and access management

Automated testing frameworks

AI orchestration frameworks

Retrieval systems

Model evaluation methodologies

Observability practices

Enterprise architecture patterns

Integration strategies

Education

Bachelor's or Master's degree in Computer Science or related

Job description

We are seeking a highly experienced Forward Deployed Engineer & Agentic AI Solution Architect to lead the design, development, and deployment of innovative Agentic AI solutions within the hospitality and hotel industry. This is a senior, hands-on role that combines business consulting, solution architecture, and technical leadership to drive measurable business outcomes in Revenue Management.

Working closely with Revenue Management leaders, business stakeholders, and technology teams, you will be responsible for identifying high-value opportunities for Agentic AI, Generative AI, predictive analytics, workflow automation, and process optimization. You will lead engagements from opportunity assessment and solution design through production deployment and value realization.

This role requires a strong blend of strategic thinking and hands-on engineering expertise, with the ability to move seamlessly between executive discussions, solution architecture, and technical implementation.

Key Responsibilities

Business & Solution Leadership

• Partner with Revenue Management and commercial leaders to identify business challenges, opportunities, and transformation priorities.
• Challenge existing operating models and processes to uncover areas where AI and automation can generate measurable value.
• Define and maintain a strategic roadmap for Agentic AI and automation initiatives aligned with business objectives.
• Establish business baselines and success metrics, including effort reduction, cycle time improvements, forecasting accuracy, exception handling, adoption, and commercial impact.
• Translate business goals into clearly defined KRAs, OKRs, and measurable outcomes.
• Own end-to-end architecture for Agentic AI solutions, including:
• Multi-agent design and orchestration
• Tool and API integrations
• Retrieval-Augmented Generation (RAG)
• Memory and contextual reasoning
• Guardrails, governance, and compliance mechanisms
• Monitoring, observability, and fallback strategies
• Define target operating models covering business users, AI agents, data platforms, and enterprise applications.
• Make architecture decisions balancing scalability, maintainability, performance, security, cost, and business value.
• Create reusable reference architectures, implementation patterns, and technical standards.
• Lead discovery workshops, architecture assessments, and rapid prototyping initiatives.
• Drive solutions from concept and proof-of-value through production deployment and operational adoption.
• Serve as a hands-on engineer capable of building prototypes, pilots, and production-ready solutions.
• Provide technical leadership and guidance to engineering teams, implementation partners, and delivery stakeholders.
• Review technical designs, code, integrations, and deployment approaches to ensure quality and scalability.
• Remove delivery obstacles and support successful execution across cross-functional teams.
• Lead integrations across:
• Property Management Systems (PMS)
• Revenue Management Systems (RMS)
• Business Intelligence platforms
• CRM and operational applications
• Ensure compliance with enterprise requirements for security, privacy, identity management, auditability, and Responsible AI.

Governance & Operational Excellence

• Establish standards and controls for:
• Prompt and model lifecycle management
• Latency and performance management
• Incident response and rollback procedures
• Observability and operational monitoring
• Drive benefit realization processes to ensure delivered solutions generate measurable business outcomes.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, Information Systems, or a related field.
• 10+ years of experience in software engineering, data engineering, AI/ML, enterprise architecture, or solution engineering.
• Proven experience leading complex technology initiatives from strategy and architecture through production deployment.
• Hands-on experience designing and implementing Agentic AI and Generative AI solutions.
• Strong expertise in:
• Python
• SQL
• REST APIs and enterprise integrations
• Event-driven architectures
• Identity and access management
• Automated testing frameworks
• Experience with AI orchestration frameworks, retrieval systems, model evaluation methodologies, and observability practices.
• Strong understanding of enterprise architecture patterns and integration strategies.
• Demonstrated ability to define business baselines, value metrics, KPIs, KRAs, and benefit realization frameworks.