At NiCE, we don’t limit our challenges. We challenge our limits. Always. We’re ambitious. We’re game changers. And we play to win. We set the highest standards and execute beyond them. And if you’re like us, we can offer you the ultimate career opportunity that will light a fire within you.
So, What's the Role All About?
We are looking for a Specialist Software Architect to lead the architectural vision, design, and evolution of our AI-driven and Conversational Solutions platform. This role demands deep hands-on expertise in Python, AWS Cloud services, AWS Knowledge Hub, and multiple Knowledge Base technologies, along with proven experience designing simplified, scalable, and resilient architectures using microservices and AWS-native services.
You will play a critical role in shaping the technical foundation of our Conversational AI platform — one that handles millions of interactions per day, meets strict SLAs (99.99%), and supports zero-downtime deployments, robust disaster recovery, and enterprise-grade AI orchestration. You will be the go-to architect for proposing pragmatic, simplified designs that balance innovation with operational excellence.
How Will You Make an Impact?
Architecture & System Design:
- Own and define the end-to-end architecture of the Conversational AI and Knowledge platform, covering AI model integration layers, data stores, knowledge bases, and external integrations.
- Design enterprise-scale, cloud-native, microservices-based architectures capable of handling high concurrency, burst traffic, and real-time conversational workloads.
- Propose simplified, cost-effective architectural designs leveraging AWS-native services — avoiding over-engineering while ensuring scalability and resilience.
- Define reference architectures, architectural blueprints, and non-functional requirements (NFRs) for performance, reliability, security, and maintainability.
- Drive event-driven and asynchronous architectures using AWS-native services such as SQS, SNS, EventBridge, and Step Functions.
- Define best practices for microservices design, domain-driven design (DDD), API design (REST, async/event APIs), and AI integration patterns.
- Review and guide complex application-level designs, critical code paths, and AI pipeline architectures.
AI & Conversational Solution Architecture:
- Architect and evolve AI-driven Conversational solutions integrating large language models (LLMs), prompt engineering patterns, and enterprise AI orchestration frameworks.
- Design and implement Knowledge Base solutions using AWS Knowledge Hub, vector databases, RAG (Retrieval-Augmented Generation) architectures, and other knowledge management technologies.
- Define AI model integration strategies — including model selection, fine-tuning approaches, embedding pipelines, and response quality frameworks.
- Drive conversational UX architecture, ensuring seamless, context-aware, and low-latency interaction flows.
- Evaluate and recommend AI tooling, platforms, and frameworks aligned with business needs (e.g., AWS Bedrock, LangChain, OpenAI, Anthropic, Kore.ai, Dialogflow).
- Lead the design of multi-turn conversation management, intent resolution, and fallback handling architectures.
AWS Cloud & Microservices Architecture:
- Architect and optimise solutions using AWS services including but not limited to Lambda, API Gateway, SQS, SNS, Step Functions, DynamoDB, Aurora Serverless, S3, Bedrock, and Kendra.
- Design cost-efficient, elastic scaling strategies aligned with unpredictable conversational AI workloads.
- Lead cloud governance, environment isolation, multi-account strategy, and infrastructure-as-code (IaC) practices.
- Define CI/CD pipeline standards, DevOps practices, and containerisation approaches (Docker, Kubernetes) for AI workload deployments.
- Drive microservices decomposition strategies — identifying service boundaries, inter-service communication patterns, and data ownership models.
Scalability, Resilience & Disaster Recovery:
- Design for extreme scale — high concurrent users, high TPS, and real-time AI inferencing demands.
- Own resilience strategies including multi-AZ and multi-region architectures, active-active or active-passive DR setups, and graceful degradation mechanisms.
- Define and validate RPO/RTO goals, conduct chaos testing, and lead DR drills.
- Ensure zero-downtime deployment capabilities through blue/green, canary, and rolling deployment strategies.
Security, Compliance & Reliability:
- Embed security by design across all AI and data architecture layers — covering authentication, authorisation, data privacy, encryption, and model safety guardrails.
- Support compliance requirements (SOC2, ISO, GDPR) from an architectural standpoint, particularly around AI data handling and knowledge base access controls.
- Partner with SRE and DevOps teams on observability, logging, distributed tracing, and alerting for AI workloads.
- Define SLIs, SLOs, and capacity planning models for conversational AI services.
Technical Leadership & Collaboration:
- Act as a technical mentor and trusted advisor to senior engineers, tech leads, and implementation teams.
- Lead architecture reviews, design councils, and technical decision forums — championing simplicity, pragmatism, and long-term maintainability.
- Partner closely with Product Management, AI/ML teams, and delivery teams to balance innovation with execution feasibility.
- Drive the long-term AI architecture roadmap and proactively reduce technical debt.
Have You Got What It Takes?
Experience & Education:
- Bachelor's degree in Computer Science, Information Systems, Electrical Engineering, or equivalent work experience.
- 10+ years of professional software engineering experience, with at least 4–5 years in a software architect or principal engineer role.
- Demonstrated experience designing and delivering AI-driven or Conversational AI platforms at enterprise scale.
Technical Expertise:
- Deep hands-on experience with Python — including AI/ML libraries, API development, and automation scripting.
- Strong expertise in AWS Cloud services — particularly those relevant to AI workloads: Bedrock, Kendra, Lambda, API Gateway, SQS, SNS, Step Functions, DynamoDB, S3, and Aurora Serverless.
- Hands-on experience with AWS Knowledge Hub and multiple Knowledge Base technologies including vector databases, document stores, and semantic search platforms.
- Proven experience designing microservices architectures — including service decomposition, inter-service communication (REST, gRPC, event-driven), and distributed data management.
- Strong understanding of:
- RAG (Retrieval-Augmented Generation) architectures and embedding pipelines
- Prompt engineering and LLM integration patterns
- Modern authentication standards (OAuth2, OIDC, SAML)
- Web APIs — REST and async/event API design
- Databases (SQL/NoSQL) and data integration patterns
- Experience with CI/CD pipelines, DevOps practices, and containerisation (Docker, Kubernetes).
- Familiarity with AI tooling and platforms such as AWS Bedrock, LangChain, OpenAI, Anthropic, Dialogflow, or Kore.ai.
- Experience with GenAI and Agentic AI application development.
Architecture & Scale:
- Demonstrated success designing systems for high traffic, low latency, and high availability at global scale.
- Deep experience with resilience, disaster recovery, and failover design in cloud-native environments.
- Strong track record of proposing simplified, pragmatic architectural solutions that avoid unnecessary complexity.
- Experience with event-driven systems, message queues, and streaming architectures.
- Strong understanding of cloud networking, caching strategies, and data modelling for AI workloads.
Good to Have:
- Experience with CCaaS or real-time communication platforms (e.g., NICE CXone).
- Exposure to multi-region SaaS deployments and hybrid serverless/container architectures.
- Familiarity with OpenSearch or Elasticsearch for conversational data search and analytics.
- Experience with cost optimisation strategies at scale on AWS.
- Knowledge of frontend technologies (JavaScript/TypeScript, React) for full-stack architecture awareness.
What's in It for You?
Join an ever-growing, market-disrupting, global company where the teams — comprised of the best of the best — work in a fast-paced, collaborative, and creative environment. As the market leader, every day at NICE is a chance to learn and grow, and there are endless internal career opportunities across multiple roles, disciplines, domains, and locations. If you are passionate, innovative, and excited to constantly raise the bar, you may just be our next NiCEr!
Enjoy NiCE-FLEX! At NICE, we work according to the NiCE-FLEX hybrid model, which enables maximum flexibility — 2 days working from the office and 3 days of remote work each week. Office days focus on face-to-face collaboration where teamwork and creative thinking generate innovation, new ideas, and a vibrant, interactive atmosphere.
Requisition ID: 10787
Reporting Into: Director , Engineering
Role Type: Individual Contributor
About NiCE
NICE Ltd. (NASDAQ: NICE) software products are used by 25,000+ global businesses, including 85 of the Fortune 100 corporations, to deliver extraordinary customer experiences, fight financial crime and ensure public safety. Every day, NiCE software manages more than 120 million customer interactions and monitors 3+ billion financial transactions.
Known as an innovation powerhouse that excels in AI, cloud and digital, NiCE is consistently recognized as the market leader in its domains, with over 8,500 employees across 30+ countries.
NiCE is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, age, sex, marital status, ancestry, neurotype, physical or mental disability, veteran status, gender identity, sexual orientation or any other category protected by law.
