Forward-Deployed AI Architect

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Forward-Deployed AI Architect based in France. Take a leading role in delivering an AI-assisted operations platform designed to streamline complex travel disruption management workflows. You will transform operational knowledge, existing software, and business requirements into a reliable, testable solution that integrates AI capabilities with established systems. Working at the intersection of AI engineering, software architecture, and operational delivery, you will own the technical approach from discovery through implementation and evaluation. You will collaborate directly with business experts, client technology partners, and engineering teams to ensure solutions are practical, maintainable, and measurable. The role emphasizes hands-on technical leadership, human oversight, traceable decisions, and evidence-based delivery rather than architecture advice alone. This remote contract opportunity offers the chance to solve complex real-world problems while shaping an AI-enabled platform for enterprise operations.

You will lead technical delivery, validate critical dependencies, and ensure that the platform meets agreed operational and engineering standards. Working closely with the engagement lead, client stakeholders, and engineers, you will turn discovery findings into implementable specifications and demonstrate measurable progress throughout delivery. Establish a reliable technical baseline: Inspect existing code, infrastructure, APIs, and operational workflows before estimating development effort. Translate discovery findings into clear specifications, acceptance criteria, source references, inputs, outputs, and exclusions. Validate requirements and assumptions: Distinguish confirmed requirements from recommendations and assumptions. Resolve contradictions with the appropriate stakeholders rather than implementing ambiguous requirements without approval. Prove critical integrations early: Build and review essential components, guide engineers, and demonstrate an end-to-end workflow in the client's test environment, from receiving a request and retrieving operational data to generating recommendations, obtaining human approval, and completing system handoffs. Verify integration readiness: Validate API access, write permissions, event contracts, error handling, and downstream system dependencies. Confirm that components work together rather than relying solely on documentation or isolated tests. Design maintainable business rules: Separate operational facts, business policies, and software logic. Work with designated business owners to define rule precedence, exceptions, validation, and approval processes. Manage rule changes and human oversight: Keep draft and inferred rules separate from approved policies. Enable versioned updates, historical replay, traceable approvals, and rollback without requiring a software release. Escalate cases that cannot be resolved confidently through established rules. Own engineering quality and evaluation: Review and test code, including AI-generated code, against the agreed architecture. Establish automated CI checks, integration tests, representative operational scenarios, and production monitoring. Ensure traceability and operational resilience: Track the exact application, rule, and data versions used during evaluations. Implement decision logs, access controls, failure recovery, and appropriate observability. Define readiness and performance measures: Agree on workflow quality, latency, operating costs, and test-readiness criteria with the client and engineering team. Provide reproducible evaluation results and documented limitations to support informed Go/No-Go decisions. Communicate technical progress and risks: Maintain concise architecture documentation and decision records. Escalate blockers with supporting evidence, clear ownership, required decisions, and delivery impact. Support realistic delivery planning: Assess feasibility before commitments are made, propose simpler alternatives when appropriate, and revise estimates as assumptions or dependencies change. Deliver maintainable outcomes: Demonstrate working increments, distinguish prototypes from fully integrated functionality, and provide practical documentation and handover materials for ongoing maintenance. Requirements: You are a hands-on technical leader who can combine strong software engineering skills with sound judgment about AI-enabled workflows and enterprise integrations. You can work through ambiguity, validate assumptions with evidence, and communicate technical trade-offs clearly to both business and engineering stakeholders. Demonstrated experience taking an applied AI or LLM-enabled workflow beyond the prototype stage and into operational use. Strong hands-on software engineering, solution architecture, API integration, and code-review capabilities. Experience translating incomplete, ambiguous, or conflicting discovery findings into implementable specifications and testable acceptance criteria. Sound judgment in choosing between structured business rules, retrieval-based approaches, AI reasoning, and human review, with a clear understanding of their respective limitations and failure modes. Practical experience with evaluation datasets, regression testing, continuous integration, and production observability. Ability to establish automated quality checks and evaluate systems using representative operational scenarios. Experience validating technical dependencies and integration requirements before committing to delivery estimates. Strong analytical and problem-solving skills, including the ability to challenge assumptions constructively and explain alternative approaches. Excellent written and verbal communication skills, with the ability to maintain clear technical documentation and communicate progress, risks, and decisions. Realistic estimation and planning skills, based on verified dependencies, available engineering capacity, and explicit assumptions. Ability to collaborate effectively with business stakeholders, client technology partners, engineering teams, and delivery leadership. Willingness to remain involved throughout discovery, implementation, testing, and evaluation, taking ownership of technical quality and delivery readiness. Nice to have: Experience with exception-heavy operational workflows or business-rule systems. Familiarity with travel, hospitality, or logistics operations. Experience deploying AI solutions on AWS. Availability to attend an in-person working session in Milan. Benefits: Remote contract opportunity, with the role available in Spain and other specified European countries. High-impact technical leadership role with ownership of the solution from discovery through implementation and evaluation. Opportunity to deliver practical AI solutions addressing complex, real-world enterprise operational challenges. Close collaboration with experienced engineers, operational experts, client technology partners, and delivery leadership. Scope to influence technical architecture, engineering standards, evaluation practices, and maintainable AI-enabled workflows. Opportunity to build solutions emphasizing human oversight, traceability, reliability, and measurable business outcomes. Compensation: No salary range is specified in the provided job description. Logistics: An in-person working session in Milan is required. Candidates should communicate their earliest start date, realistic weekly availability, and ability to travel.