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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.

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.

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 a Senior Data Science Researcher in our Workforce Management group, you will be part of a cross-sectional team working at the intersection of machine learning, GenAI, agentic AI, ML-Ops and Operations Research. You will develop the next generation of our companys Workforce Management solution for our customers contact centers - forecasting work volume, scheduling agent shifts, managing time-off requests, and owning the full lifecycle of the work schedule, in a high-stakes production environment serving many customers. Our solution has been recognized as the market leader for over 10 years.
How will you make an impact?
Developing end-to-end ML systems, tailored to specific project needs, to train and serve production-level models in a high-stakes environment.
Deploying GenAI and agentic AI systems to customers in production, improving on existing solutions or creating new services from scratch.
Designing and building agentic AI flows - tool use, multi-step reasoning, and orchestration.
Forecasting work volume and optimizing shift schedules using time-series methods and mathematical optimization.
Integrating new features and solutions into large existing software systems, stringing multiple disciplines together.
Running unstructured evaluation processes - finding noteworthy phenomena, experimenting, and feeding conclusions back to the team.
Owning projects end-to-end, leading team members and colleagues to efficient planning and delivery.

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.

our company enables organizations to address todays consumer and employee expectations by delivering effortless, consistent, and personalized digital-first experiences with CXone, the worlds leading cloud customer experience platform.
CSA team is dedicated to developing groundbreaking AI products that are transforming the industry. We promote a culture of collaboration, technical excellence, and the adoption of advanced technologies at scale.
We are looking for a Lead DevOps Engineer to join our CSA Infrastructure group. In this role, you will take a technical leadership position, driving the design, scalability, security, and operational excellence of our cloud platforms, while mentoring engineers and shaping DevOps best practices across teams.
How will you make an impact?
Lead the design, evolution, and operation of large-scale cloud infrastructure on AWS and Azure, ensuring high availability, security, resilience, and cost efficiency
Drive Infrastructure as Code (IaC) strategy and quality, ensuring consistency, reusability, and maintainability across environments and development groups
Act as a technical authority for troubleshooting complex production issues and leading root-cause analysis
Collaborate closely with development, QA, security, and product teams to align infrastructure with business and product needs
Mentor and guide DevOps engineers, fostering a culture of ownership, learning, and continuous improvement
Lead initiatives around observability, monitoring, alerting, and incident response
Proactively identify risks, technical debt, and optimization opportunities
Evaluate, introduce, and scale new tools, technologies, and AI-driven automation to improve efficiency and reliability.

As a Lead Software Engineer, you will be at the heart of building our Cloud Analytics Infrastructure group.
If youre talented, highly motivated and passionate about building modern cloud architectures and enjoy solving complex engineering challenges, this role is for you.
In this role, you will orchestrate AI agents to accelerate engineering workflows and deliver innovative AI‑driven features directly to customers.
Youll work in a fast‑paced, agentic environment where experimentation, ownership, and initiative are not just encouraged-theyre expected.
If you excel as an engineer, exploring the boundaries of AI‑assisted development, and want to influence the future of how engineering teams work with autonomous agents, this role is tailor‑made for you.
How will you make an impact?
Drive engineering excellence through AI‑augmented workflows and agentic development patterns.
Ensure high-quality deliverables and efficient project execution and continuous improvement.
Lead features design and implementations, set the bar for the team standards and advise on tech. Selection, show initiative in driving technical direction and team collaboration.
Demonstrate strategic thinking and a long-term vision for scalable solutions.
Champion continuous improvement and high‑velocity delivery in an innovative, fast‑moving environment.

As a Senior AI&ML Researcher in our Workforce Management group, you will be part of a cross-sectional team working at the intersection of machine learning, GenAI, agentic AI, ML-Ops and Operations Research. You will develop the next generation of our companys Workforce Management solution for our customers contact centers - forecasting work volume, scheduling agent shifts, managing time-off requests, and owning the full lifecycle of the work schedule, in a high-stakes production environment serving many customers. Our solution has been recognized as the market leader for over 10 years.
How will you make an impact?
Developing end-to-end ML systems, tailored to specific project needs, to train and serve production-level models in a high-stakes environment.
Deploying GenAI and agentic AI systems to customers in production, improving on existing solutions or creating new services from scratch.
Designing and building agentic AI flows - tool use, multi-step reasoning, and orchestration.
Forecasting work volume and optimizing shift schedules using time-series methods and mathematical optimization.
Integrating new features and solutions into large existing software systems, stringing multiple disciplines together.
Running unstructured evaluation processes - finding noteworthy phenomena, experimenting, and feeding conclusions back to the team.
Owning projects end-to-end, leading team members and colleagues to efficient planning and delivery.

We are looking for a Senior Software Engineer to join the Data Repositories team, part of the Actimize NXT Gen PaaS/SaaS engineering group. In this role, you will design and build core backend services and data infrastructure powering Actimizes cloud native financial crime solutions.
Our next generation platform is being built from the ground up on AWS and will serve developers, data engineers, and data scientists at the worlds leading financial institutions. This is a unique opportunity to shape foundational platform components, influence architecture, and work with cutting-edge cloud and data technologies at scale.
How will you make an impact?
Lead, design, and implement backend/datacentric components for a cloud native platform on AWS.
Own end-to-end delivery: from requirements and architecture to coding, testing, deployment, and monitoring.
Build robust, scalable, and observable services used across the Actimize NXT Gen ecosystem.
Be a technical authority within the team: guide design discussions, perform code reviews, mentor developers.
Troubleshoot complex issues across distributed systems, data stores, and microservice architectures.
Drive innovation: evaluate new AWS services, frameworks, and data technologies; introduce improvements proactively.
Collaborate in an Agile environment with product managers, architects, DevOps, and cross functional engineering teams.
Ensure high availability, performance, and enterprise grade quality across components you own.

As a Senior Software Engineer, you will be at the heart of building our companys next‑generation Workforce Management platform - an advanced cloud‑native solution enhanced with intelligent, AI‑powered capabilities.
In this role, you will build full‑stack features, orchestrate AI agents to accelerate engineering workflows, and deliver innovative AI‑driven features directly to customers.
Youll work in a fast‑paced, agentic environment where experimentation, ownership, and initiative are not just encouraged-theyre expected.
If you excel as an engineer, exploring the boundaries of AI‑assisted development, and want to influence the future of how engineering teams work with autonomous agents, this role is tailor‑made for you.
How will you make an impact?
Drive engineering excellence through AI‑augmented workflows and agentic development patterns.
Develop end to end cloud features on top of AWS.
Optimizing components for maximum performance.
Ensure high-quality deliverables and efficient project execution and continuous improvement.
Lead features design and implementations.
advise on tech. selection, show initiative in driving technical direction and team collaboration.
Demonstrate strategic thinking and a long-term vision for scalable solutions.
Champion continuous improvement and high‑velocity delivery in an innovative, fast‑moving environment.

we are looking for talented, highly motivated Senior Java Software Engineers to join our Cloud Analytics Infrastructure group. If youre passionate about building modern cloud architectures and enjoy solving complex engineering challenges, this role is for you. You will help design and develop large scale, AWS based systems that power the global company CXone cloud platform. The applications you build are deployed across multiple regions and support hundreds of enterprise customers worldwide.
How will you make an impact?
Design and implement scalable microservices using AWS technologies.
Develop high‑quality services in a Java Spring Boot environment.
Participate in the full feature lifecycle-from design to implementation.
Analyze requirements and create clear, comprehensive design documentation.
Review and refine designs with peers and stakeholders.
Collaborate closely with the team to iterate on architecture and features.
Apply agile methodologies with AI tools to deliver reliable, high-impact capabilities efficiently.