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Build and deploy production-grade AI solutions, including LLM agents, multi-agent workflows, RAG systems, classical ML, and speech models. Develop reliable, secure, observable, and scalable AI platforms using strong software engineering and MLOps practices. Own solutions from client scoping through monitoring and continuous improvement, collaborate with technical and business stakeholders, mentor engineers, and drive innovation in enterprise AI.

Lead complex AI projects from scoping through production go-live for Swiss enterprise clients. Manage scope, budgets, timelines, governance, risks, stakeholders, and delivery teams while connecting business priorities with technical realities. Serve as the primary client contact, resolve blockers, shape roadmaps, support presales, and improve delivery standards. The role requires strong AI fluency, project management expertise, consulting skills, and communication with business and technical stakeholders.

Design, build, and deploy production-grade AI solutions including LLM agents, multi-step workflows, RAG, classical ML, and speech models. Develop Python-based services, MLOps pipelines, evaluation systems, observability, and scalable cloud deployments. Ensure security, compliance, reliability, and cost efficiency for regulated enterprise environments. Collaborate with clients and cross-functional teams, own solutions end to end, mentor engineers, and contribute to reusable AI accelerators and innovation initiatives.

Advise financial services and insurance leaders on AI-enabled business models, data and AI strategy, governance, operating models, and transformation priorities. Structure complex challenges, conduct market analysis, develop roadmaps, lead transformation workstreams, coach colleagues, and support business development through proposals, thought leadership, and reusable methodologies. The role involves international client travel, primarily to the UK and France.

Lead and grow a software engineering team delivering scalable, high-quality AI solutions for banking and insurance clients. Responsibilities include defining architecture, establishing development best practices, managing team performance and growth, resolving technical obstacles, collaborating cross-functionally, and ensuring successful client delivery within agreed timelines.

Design, build, optimize, deploy, and monitor production AI/ML solutions, especially LLM and VLM applications. Develop model integrations, APIs, MLOps pipelines, RAG systems, and scalable serving infrastructure. Apply software engineering, testing, CI/CD, observability, security, and compliance practices. Own model lifecycles from data preparation and research through production maintenance. Collaborate with engineers, project managers, clients, and stakeholders while mentoring junior engineers and evaluating emerging AI techniques.

Provide first-line IT support for office and remote employees, resolving hardware, software, network, and account issues. Manage onboarding and offboarding, Microsoft 365, macOS, Atlassian, device and software inventory, licensing administration, and IT documentation. Build workflow automations, use AI tools, support data security, and escalate complex or recurring issues. The role offers hybrid work and growth toward systems administration, security, and licensing responsibilities.

Lead business analysis for complex AI and data projects, translating stakeholder needs into requirements, workflows, user stories, and solution designs. Responsibilities include process and data modeling, exploratory data analysis, backlog ownership, scope management, testing and UAT coordination, client adoption support, and pre-sales contributions. The role bridges business stakeholders with architects, engineers, and data scientists while supporting AI transformations for Swiss financial and insurance clients.

Hands-on technical lead responsible for designing, coding, and delivering enterprise data and AI systems. Leads cross-functional engineering teams, defines architectures, reviews designs and code, mentors engineers, and enables scalable AI development and operations. The role addresses complex enterprise ecosystems, modernization, cybersecurity, data governance, responsible AI, compliance, and regulated environments. It also supports executive stakeholder relationships, proposals, and expansion of data and AI platform capabilities.

Design, implement, and maintain scalable Azure and AWS cloud infrastructure. Build CI/CD pipelines, manage Kubernetes and Docker environments, implement Terraform-based infrastructure as code, and support GitOps deployments. Monitor performance, troubleshoot issues, apply networking security controls, and collaborate with development and cross-functional teams. The role also includes mentoring junior engineers and driving continuous infrastructure improvement in a client-facing consultancy environment.