Lead Security Engineer responsible for developing and enhancing security strategies, red teaming programs, and solution designs for AI and software architectures, ensuring adversarial resilience and compliance with industry standards.
Compensation
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions.
Responsibilities
Develop and enhance security strategies, red teaming programs, and solution designs
Design secure, high-quality AI and software architectures
Reduce AI and LLM security vulnerabilities
Collaborate with stakeholders across product, data science, cyber, legal, and risk
Conduct discovery, threat modeling, and adversarial testing on generative AI, RAG pipelines, and ML systems
Requirements
Nice to have: AI red teaming exercises
Nice to have: AI security/red teaming tools and frameworks
Nice to have: contributions to AI security or open-source security projects
Lead the strategy, build, and evolution of a multi-cloud AI platform and enterprise compute services to accelerate discovery and development of life-changing medicines.
Compensation
competitive pay, bonus opportunities, and learning and development opportunities
Responsibilities
Define how AI and machine learning services are used across AWS, Azure and GCP
Manage managed services such as SageMaker, Azure ML and Vertex AI through architecture and Infrastructure as Code
Lead enterprise compute strategy balancing performance, cost, resilience and compliance
Unify cloud-native AI services into a consistent platform model with shared governance and guardrails
Build, coach, and challenge a high-performing team of AI platform and DevOps specialists
We are looking for a Manager who leads strategy and architecture projects focused on GenAI solutions. You will own the design of architectures and solutions end to end, balancing business value, technology choices and economics across every dimension of the decision.
Locations (2)
Zurich, Zurich, Switzerland
Lausanne, Vaud, Switzerland
Responsibilities
Lead strategy and architecture projects on GenAI, from scoping and business case through to solution design and rollout oversight.
Own project plans, budgets, risks and quality, ensuring delivery against client objectives.
Shape proposals, estimates and demos, and identify follow-on opportunities with clients.
Design GenAI architectures and solutions: RAG, agentic systems, multi-agent orchestration, MCP and A2A integration, copilots and assistants.
Select and combine cloud-native AI services (e.g. Azure AI Foundry, Copilot Studio, Vertex AI, Bedrock, Databricks) with third-party and custom components.
Requirements
Forward Deployed Engineer
Accenture Infrastructure and Capital Projects, LLC · Posted Nov 3, 2026
A production engineer who works embedded inside a client's enterprise to transform legacy infrastructure & Application estates into AI-ready, cloud/Hybrid platforms and Modernized Infrastructure.
Responsibilities
Embed directly with client infrastructure and engineering teams to design, execute, and operationalize end-to-end transformation spanning cloud foundation, hyperconverged infrastructure, platform engineering, application modernization, database transformation, SAP, network and security, and AI platform deployment.
Accountable for production outcomes — platform reliability, time-to-value, adoption, and scalability.
Move from ambiguous infrastructure problems to working production environment through rapid iteration.
Organize the deployment of AI workflows and architectures across diverse AI and technology platforms. Facilitate solution design across enterprise technology stack to integrate into the ecosystem of AI models and multi provider platforms.
Responsibilities
Embed directly with client infrastructure and engineering teams to design, execute, and operationalize end-to-end transformation — spanning cloud foundation, hyperconverged infrastructure, platform engineering, application modernization, database transformation, SAP, network and security, and AI platform deployment.
Accountable for production outcomes — platform reliability, time-to-value, adoption, and scalability — measured against business metrics, not project milestones.
Move from ambiguous infrastructure problems to working production environment through rapid iteration: days to validated architecture, weeks to production-ready deployment.
Execute application migration hands-on — rehost (lift & shift), re-platform (lift & optimize), and redeploy — applying the right strategy per workload to land on an AI-ready, modernized target platform.
Architect and implement network and security foundations: Zero Trust, SASE/SSE, micro-segmentation, container security, and application AI governance across enterprise environments.
Requirements
15 years full time education
Nice to have: Cloud Automation DevOps
Nice to have: Cloud Strategy and Assessment
Nice to have: Docker Kubernetes Architecture
Forward Deployed Engineer
Accenture Infrastructure and Capital Projects, LLC · Posted Nov 3, 2026
A Forward Deployed Infrastructure Transformation Engineer is a production engineer working embedded inside a client's enterprise to transform legacy infrastructure and Application estates into AI-ready, cloud/Hybrid platforms and Modernized Infrastructure, focusing on time-to-value, reliability, adoption, and scalability.
Responsibilities
Organize the deployment of AI workflows and architectures across diverse AI and technology platforms.
Facilitate solution design across enterprise technology stack to integrate into the ecosystem of AI models and multi provider platforms.
Embed directly with client infrastructure and engineering teams to design, execute, and operationalize end-to-end transformation.
Accountable for production outcomes — platform reliability, time-to-value, adoption, and scalability.
Move from ambiguous infrastructure problems to working production environment through rapid iteration.
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