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We are seeking a Senior Cloud Architect to join our company IT AI and own the Azure cloud and AI infrastructure that powers intelligent automation across the enterprise.
This is a deeply hands-on role. You will design, build, and govern the full-stack architecture, from enterprise networking and private connectivity up to AI orchestration, delivering the platform to the development teams while partnering with the Systems, Network, and Security teams to connect, govern, and approve every design before it goes live.
How will you make an impact? 
You will own our company's IT AI cloud architecture end-to-end, combining hands-on Azure engineering with architectural leadership across these areas:
Cloud Architecture Design & Implementation
Own the end-to-end Azure architecture for AI workloads (LLMs, RAG, vector DBs, Graph, agents, MLOps) across all platform layers, with reference designs and ADRs.
Enterprise Networking & Private Connectivity
Design hub-and-spoke VNets, private connectivity (Private Endpoints, Private DNS), firewall/ingress patterns, and isolated multi-environment topology (prod / dev / test).
AI Developer Toolchain & Platform Engineering
Architect the developer AI stack, Azure AI Foundry, GitHub Copilot, Claude/MCP, Models Gateway, and scaled tooling distribution (MDM / Intune).
CI/CD, DevOps & Platform Automation
Establish CI/CD (GitHub Actions), Infrastructure-as-Code (Terraform / Bicep), and compute, MLOps/LLMOps, and FinOps practices with the DevOps team.
Identity, Security & Governance
Design IAM and auth flows (Entra ID, OIDC/JWT, API gateway validation) and the observability stack, and secure Security-team review and approval of every architecture.
Cross-functional Leadership
Act as architectural liaison across AI CoE, Development, DevOps, Infrastructure, Systems, Network, and Security; mentor engineers and own the platform roadmap.

We are seeking a Senior Cloud Architect to join our company IT AI and own the Azure cloud and AI infrastructure that powers intelligent automation across the enterprise.
This is a deeply hands-on role. You will design, build, and govern the full-stack architecture, from enterprise networking and private connectivity up to AI orchestration, delivering the platform to the development teams while partnering with the Systems, Network, and Security teams to connect, govern, and approve every design before it goes live.
How will you make an impact? 
You will own our company's IT AI cloud architecture end-to-end, combining hands-on Azure engineering with architectural leadership across these areas:
Cloud Architecture Design & Implementation
Own the end-to-end Azure architecture for AI workloads (LLMs, RAG, vector DBs, Graph, agents, MLOps) across all platform layers, with reference designs and ADRs.
Enterprise Networking & Private Connectivity
Design hub-and-spoke VNets, private connectivity (Private Endpoints, Private DNS), firewall/ingress patterns, and isolated multi-environment topology (prod / dev / test).
AI Developer Toolchain & Platform Engineering
Architect the developer AI stack, Azure AI Foundry, GitHub Copilot, Claude/MCP, Models Gateway, and scaled tooling distribution (MDM / Intune).
CI/CD, DevOps & Platform Automation
Establish CI/CD (GitHub Actions), Infrastructure-as-Code (Terraform / Bicep), and compute, MLOps/LLMOps, and FinOps practices with the DevOps team.
Identity, Security & Governance
Design IAM and auth flows (Entra ID, OIDC/JWT, API gateway validation) and the observability stack, and secure Security-team review and approval of every architecture.
Cross-functional Leadership
Act as architectural liaison across AI CoE, Development, DevOps, Infrastructure, Systems, Network, and Security; mentor engineers and own the platform roadmap.

The Chief Architect at our company Actimize owns the technical vision that holds this portfolio together. The mandate is to ensure that a wide-ranging set of products remains coherent, secure, scalable, and economical to build and operate regardless of where and how it is deployed. This is a hands-on leadership role at the intersection of deep technical authority and enterprise strategy: you will set architectural direction, resolve the hardest cross-cutting trade-offs, and raise the engineering bar across the organization.
This is the most senior individual-contributor-plus-leadership technical role in the company. You will be a trusted advisor to the executive team and the final technical authority on architecture decisions that span products.
How will you make an impact?
Architectural Vision & Strategy
Define and own the multi-year target architecture across the entire product suite, balancing product autonomy with shared platform leverage.
Establish an architecture strategy so that products can be delivered on-premise, in private cloud, in public cloud, or as pure cloud SaaS.
Drive the platform and shared-services strategy (identity, data, integration, observability, deployment tooling) that reduces fragmentation across products.
Help architects translate business and product strategy into technical roadmaps; advise the executive team on build-vs-buy, modernization, and major technology bets.
Design abstractions and packaging models that let a single product run reliably across heterogeneous environments with differing scale, network, data residency, and operational constraints.
Establish reference architectures and patterns for tenancy, configuration management, release/upgrade cadence, and feature parity across on-premise and cloud-hosted deployments.
Security, Compliance & Resilience
Embed security, privacy, and regulatory compliance into the architecture by design - addressing the standards relevant to financial services (e.g., data protection, auditability, segregation, encryption, and regional data residency).
Define non-functional requirements and architectural guardrails for availability, disaster recovery, transactional integrity, performance, and observability appropriate to mission-critical financial systems.
Partner with Security, Risk, and Compliance leadership to ensure the architecture withstands audit and regulatory scrutiny across jurisdictions.
Governance & Standards
Establish and run an architecture governance function: standards, decision records, review processes, and a technology radar - proportionate enough to enable speed rather than obstruct it.
Evaluate and select core technologies, platforms, and strategic vendors; own the long-term technology stack direction.
Leadership & Influence
Lead and mentor a community of architects and senior engineers; grow architectural capability across teams.
Build consensus across product, engineering, security, operations, and commercial stakeholders, and make decisive calls when consensus isn't reachable.
Represent the company's technical vision with key customers, partners, and prospects, and in due-diligence and pre-sales conversations for strategic deals.

The Chief Architect at our company Actimize owns the technical vision that holds this portfolio together. The mandate is to ensure that a wide-ranging set of products remains coherent, secure, scalable, and economical to build and operate regardless of where and how it is deployed. This is a hands-on leadership role at the intersection of deep technical authority and enterprise strategy: you will set architectural direction, resolve the hardest cross-cutting trade-offs, and raise the engineering bar across the organization.

This is the most senior individual-contributor-plus-leadership technical role in the company. You will be a trusted advisor to the executive team and the final technical authority on architecture decisions that span products.
How will you make an impact?
Architectural Vision & Strategy
Define and own the multi-year target architecture across the entire product suite, balancing product autonomy with shared platform leverage.
Establish an architecture strategy so that products can be delivered on-premise, in private cloud, in public cloud, or as pure cloud SaaS.
Drive the platform and shared-services strategy (identity, data, integration, observability, deployment tooling) that reduces fragmentation across products.
Help architects translate business and product strategy into technical roadmaps; advise the executive team on build-vs-buy, modernization, and major technology bets.
Design abstractions and packaging models that let a single product run reliably across heterogeneous environments with differing scale, network, data residency, and operational constraints.
Establish reference architectures and patterns for tenancy, configuration management, release/upgrade cadence, and feature parity across on-premise and cloud-hosted deployments.
Security, Compliance & Resilience
Embed security, privacy, and regulatory compliance into the architecture by design - addressing the standards relevant to financial services (e.g., data protection, auditability, segregation, encryption, and regional data residency).
Define non-functional requirements and architectural guardrails for availability, disaster recovery, transactional integrity, performance, and observability appropriate to mission-critical financial systems.
Partner with Security, Risk, and Compliance leadership to ensure the architecture withstands audit and regulatory scrutiny across jurisdictions.
Governance & Standards
Establish and run an architecture governance function: standards, decision records, review processes, and a technology radar - proportionate enough to enable speed rather than obstruct it.
Evaluate and select core technologies, platforms, and strategic vendors; own the long-term technology stack direction.
Leadership & Influence
Lead and mentor a community of architects and senior engineers; grow architectural capability across teams.
Build consensus across product, engineering, security, operations, and commercial stakeholders, and make decisive calls when consensus isn't reachable.
Represent the company's technical vision with key customers, partners, and prospects, and in due-diligence and pre-sales conversations for strategic deals.

As AI Quality Architect, you are the person who makes quality native to the agentic SDLC. You design the systems, standards, and intelligence layers that ensure every stage of an AI-accelerated pipeline - from requirement ingestion to autonomous deployment - is observable, trustworthy, and continuously improving. You don't retrofit testing onto AI workflows; you architect quality into them from the ground up.
How will you make an impact?
Agentic Quality Architecture
Design the end-to-end quality architecture for agentic SDLC pipelines - spanning requirement analysis, code generation, test creation, execution, triage, and release gates
Define how quality agents are orchestrated: which decisions they own autonomously, which require human-in-the-loop checkpoints, and how confidence thresholds govern both
Architect multi-agent quality workflows: requirement validation agents, test generation agents, failure triage agents, and regression analysis agents working in coordinated pipelines
Establish trust and verification models for agent-produced artifacts - test code, assertions, coverage reports, and defect analyses must all be auditable and traceable
Own the architectural patterns for quality feedback loops between agents: how a deployment agent learns from a triage agent's findings, and how that signal improves future generation
AI-Native Test Engineering Platform
Design and own the LLM-powered test generation platform - from natural language requirement ingestion to executable, maintainable test output
Architect the evaluation harness that continuously measures test generation quality: coverage delta, false-positive rates, assertion accuracy, and maintenance burden over time
Build the self-healing test infrastructure layer - agents that detect broken selectors, drifted APIs, or changed behaviors and propose or apply fixes autonomously
Define the prompt engineering standards, context injection patterns, and RAG architectures that ground test generation agents in real codebase context
Architect test artifact governance: versioning, ownership attribution (human vs. agent), rollback capability, and confidence scoring for every generated artifact
Quality Gates in Autonomous Pipelines
Design intelligent, adaptive quality gates that operate at the speed of agentic CI/CD - gates that reason about risk, not just pass/fail thresholds
Build risk-scoring models that dynamically adjust gate strictness based on change scope, code origin (human vs. AI-generated), historical failure patterns, and deployment context
Architect the observability layer for agentic pipelines: what signals indicate a pipeline agent is making poor quality decisions, and how are those signals surfaced in real time
Define the integration patterns between quality gates and orchestration platforms (LangChain, LlamaIndex, custom agent frameworks) used across the engineering org
Establish rollback and circuit-breaker patterns for autonomous deployments triggered by quality signal degradation.

As AI Quality Architect, you are the person who makes quality native to the agentic SDLC. You design the systems, standards, and intelligence layers that ensure every stage of an AI-accelerated pipeline - from requirement ingestion to autonomous deployment - is observable, trustworthy, and continuously improving. You don't retrofit testing onto AI workflows; you architect quality into them from the ground up.
How will you make an impact?
Agentic Quality Architecture
Design the end-to-end quality architecture for agentic SDLC pipelines - spanning requirement analysis, code generation, test creation, execution, triage, and release gates
Define how quality agents are orchestrated: which decisions they own autonomously, which require human-in-the-loop checkpoints, and how confidence thresholds govern both
Architect multi-agent quality workflows: requirement validation agents, test generation agents, failure triage agents, and regression analysis agents working in coordinated pipelines
Establish trust and verification models for agent-produced artifacts - test code, assertions, coverage reports, and defect analyses must all be auditable and traceable
Own the architectural patterns for quality feedback loops between agents: how a deployment agent learns from a triage agent's findings, and how that signal improves future generation
AI-Native Test Engineering Platform
Design and own the LLM-powered test generation platform - from natural language requirement ingestion to executable, maintainable test output
Architect the evaluation harness that continuously measures test generation quality: coverage delta, false-positive rates, assertion accuracy, and maintenance burden over time
Build the self-healing test infrastructure layer - agents that detect broken selectors, drifted APIs, or changed behaviors and propose or apply fixes autonomously
Define the prompt engineering standards, context injection patterns, and RAG architectures that ground test generation agents in real codebase context
Architect test artifact governance: versioning, ownership attribution (human vs. agent), rollback capability, and confidence scoring for every generated artifact
Quality Gates in Autonomous Pipelines
Design intelligent, adaptive quality gates that operate at the speed of agentic CI/CD - gates that reason about risk, not just pass/fail thresholds
Build risk-scoring models that dynamically adjust gate strictness based on change scope, code origin (human vs. AI-generated), historical failure patterns, and deployment context
Architect the observability layer for agentic pipelines: what signals indicate a pipeline agent is making poor quality decisions, and how are those signals surfaced in real time
Define the integration patterns between quality gates and orchestration platforms (LangChain, LlamaIndex, custom agent frameworks) used across the engineering org
Establish rollback and circuit-breaker patterns for autonomous deployments triggered by quality signal degradation.

As a Cloud Architect, you will be the visionary architecting our companys next-generation cloud infrastructure-a resilient, scalable, and high-velocity ecosystem designed to support our intelligent, AI-powered platforms.
In this role, you will bridge the gap between complex engineering requirements and elegant cloud solutions. You will be responsible for designing sophisticated systems, pioneering DevOps excellence, and ensuring our R&D teams have the cutting-edge tools they need to deliver at pace. Youll thrive in an environment that values an automation-first mindset, where you are empowered to prototype new technologies and set the strategic direction for our global infrastructure.
How will you make an impact?
Architect Complex Systems: Design scalable, resilient cloud architectures and select the optimal technology stacks to bring them to life.
Drive Operational Excellence: Identify and execute opportunities to improve system resilience, efficiency, and the overall developer experience through aggressive automation.
Innovate & Prototype: Actively research and prototype emerging technologies that sharpen our DevOps processes and R&D delivery speed.
Technical Leadership: Lead complex build, release, and deployment initiatives, navigating dependencies across multiple stakeholders with a long-term vision.
Infrastructure as Code: Champion GitOps workflows and Infrastructure-as-Code (IaC) to ensure our production systems are secure, compliant, and highly available.
Bridge Business & Tech: Translate deep technical complexities into tangible business value, ensuring our architecture supports our companys strategic goals.

In this role, you will be shaping the future of our companys AI software stack for Neural Processing Units (NPUs). You will lead software architecture, define performance-critical components, and enable efficient execution of advanced neural networks under tight power, memory, and latency constraints.
You will work closely with hardware and system architects, software and hardware engineers, influencing both software and hardware decisions. You will design and implement major parts of our company NPU embedded solutions, actively promoting our company AI capabilities to the customers.
We are seeking a high-impact motivated Software Architect to join our team and help shape the future of our advanced neural network AI Software Toolchain over our companys AI computing processors.
Responsibilities
Lead Software Architecture specification and supervise design for the most advanced Software Toolchain handling state-of-the-art Neural Processing Unit operation.
Design and promote holistic software solutions incorporating various aspects of NPU handling: from network retraining, graph compiling and network inference execution on the embedded systems.
Collaborate proactively with Product, Architecture, VLSI and Software teams to promote software leadership over various markets and compute SoCs.
Explore and translate state-of-the-art neural network and AI applications requirements into software architecture flows, encompassing hardware, software, tools and other components.
Evaluate architecture proposals, internal and external IP features and provide influential and inspirational leadership across hardware and software to align all parties to a common vision of architecture & technology development.
Represent our company with high technical credibility in customer meetings, appropriately incorporating feedback.
Boost velocity of development teams by providing technical guidance and by constantly looking ahead to anticipate and resolve future challenges.
Conduct experiments, invent and drive development of supporting tools such as simulators, models, profilers, and other methods as required.
Engage with engineering leadership and product planning stakeholders to develop technology roadmap.

We are seeking an AI Networking Exploration Architect for our Networking Insights Group to bridge the gap between cutting-edge, hyper-scale AI workloads and the datacenter infrastructure that enables them. You will join a small, focused team of multidisciplinary engineers driving AI workload optimization through deep application understanding and end-to-end systems thinking. Your insights will directly shape our products across the full stack-from applications and software libraries to hardware architecture and physical design.

What You'll Be Doing:

Model the performance of complex AI workloads to identify bottlenecks and recommend system-level optimizations.

Translate state-of-the-art research into actionable infrastructure, software, and hardware features in partnership with architecture teams.

Rapidly master new AI domains (LLMs, generative models, multimodal systems) and distill key findings for product teams.

Incorporate your deep knowledge of AI applications into our hardware and software roadmaps.

Conduct independent research by formulating hypotheses about workload behavior and validating them through rigorous analysis.

Drive architectural innovation and network optimization by applying your domain expertise to exploratory analysis of real-world Deep Learning (DL) workloads.

We are looking for a highly skilled Advanced Development Engineer to join the Software Architecture Team. In this hands-on role, you will shape the future of large‑scale data centers through advanced simulation, high‑scale telemetry, and next‑generation infrastructure solutions. You will work at the frontier of technology - exploring, prototyping, and proving new concepts - and turn them into scalable, production‑ready foundations. Your work will span large‑scale telemetry pipelines, data integrity at extreme scale, and advanced simulation frameworks used to model, validate, and optimize complex data‑center environments.

As part of the Architecture team, you will directly influence cross‑company platforms and long‑term technology direction, while actively contributing code, frameworks, and ideas. You will also have opportunities to participate in and contribute to open‑source projects and communities.

What you'll be doing:

Discover, evaluate, and prototype emerging technologies with a strong focus on simulation, scale, and system behavior modeling.

Design, implement, and evolve high‑scale software systems integrated across the full Data Center life‑cycle.

Build advanced simulation solutions to model data‑center behavior, telemetry flows, failure scenarios, and system performance at scale.

Define and expand large‑scale telemetry and observability pipelines, ensuring accuracy, consistency, and traceability of data.

Incorporate new and diverse data sources to continuously extend the capabilities of a centralized, petabyte‑scale Data Lake.

Collaborate closely with engineering, architecture, and research teams across us to translate business and technical requirements into robust, scalable solutions.

Work side‑by‑side with architects and data scientists to design, validate, and evolve data and simulation architectures.

Contribute to defining the architecture of next‑generation monitoring, analytics, and simulation platforms for hyperscale data centers.

Extend existing platforms and actively contribute code, designs, and leadership to Open Source projects and communities.