What's the Role All About?

The Tech Manager is a senior technical leadership role responsible for driving the design, delivery, and quality of AI-driven and Conversational AI solutions across the NICE CXone ecosystem. With 15+ years of experience, you will lead and mentor a high-performing engineering team, bring deep expertise in AI models, AWS Knowledge Hub, and AWS Cloud, and serve as a key technical authority across cross-functional delivery teams. This role blends hands-on technical depth with strong people management, ensuring both engineering excellence and team growth.

How Will You Make an Impact?

Technical Leadership:

• Define and govern technical standards and best practices for AI and Conversational AI solution delivery.
• Provide hands-on guidance on the design and implementation of integrations using APIs, modern web technologies, and authentication standards.
• Lead the development of proofs of concept (PoCs) and production-ready solution components leveraging AWS Cloud, AWS Knowledge Hub, and AI/ML models.
• Drive prompt engineering, conversational design, and AI orchestration best practices across the team.
• Oversee testing, validation, and go-live activities to ensure solutions meet quality, performance, security, and usability standards.

People Management & Team Development:

• Lead, mentor, and develop a team of engineers — conducting performance reviews, supporting career growth, and fostering a culture of continuous learning.
• Define and uphold engineering standards, coding guidelines, and delivery frameworks across the team.
• Identify skill gaps and build team capability in emerging areas such as Generative AI, AWS services, and enterprise conversational platforms.
• Drive a collaborative, inclusive, and high-accountability team culture.

Technical Problem Solving & Quality:

• Diagnose and resolve complex technical challenges across SaaS applications, cloud environments, AI integrations, and data flows.
• Ensure all implementations meet enterprise-grade standards for quality, scalability, security, and performance.
• Produce and review key documentation including architecture specifications, test strategies, and deployment materials.

Delivery & Process Excellence:

• Drive Agile/Scrum delivery practices including sprint planning, retrospectives, and release management.
• Define and continuously improve engineering processes, documentation standards, and delivery frameworks.
• Align technical roadmap planning with business priorities and stakeholder expectations.
• Manage escalations effectively and maintain strong cross-functional collaboration with Implementation Engineers, Consultants, Project Managers, and Customer Success teams.

Collaboration & Stakeholder Engagement:

• Partner with senior stakeholders, customers, and cross-functional teams to translate business requirements into technical solutions.
• Participate in customer workshops, design reviews, and technical discussions — communicating architecture decisions and implementation strategies with clarity and confidence.
• Maintain transparent and consistent communication across all delivery teams.

Have You Got What It Takes?

Experience & Education:

• Bachelor's degree in Computer Science, Information Systems, Electrical Engineering, or equivalent work experience.
• 15+ years of professional experience in software engineering or technical delivery roles, with a focus on AI, digital channels, or bot/conversational applications preferred.
• 5+ years in a technical leadership or people management role (Engineering Manager, Tech Lead, or similar).

Technical & Architecture Skills:

• 7+ years of hands-on software development experience, with at least 2–3 years in a tech lead or architect capacity.
• Strong proficiency in modern programming languages such as Java, Python, C#, or JavaScript/TypeScript.
• Deep knowledge of AWS Cloud services and AWS Knowledge Hub; familiarity with Azure or GCP is a plus.
• Proven experience working with AI/ML models, Generative AI frameworks, and enterprise AI orchestration patterns.
• Strong expertise in:
• Web APIs, SOAP, and REST implementations
• Modern authentication standards (OAuth2, OIDC, SAML)
• Browser and web security (CORS, X-Frame Options)
• HTML/CSS and front-end fundamentals
• Prompt engineering and AI integration patterns
• Solid understanding of CI/CD pipelines, DevOps practices, and software architecture principles.
• Proficiency in databases (SQL/NoSQL) and data integration patterns.
• Strong understanding of conversational UX, AI-driven interfaces, and enterprise AI platforms.

Leadership & People Management:

• Demonstrated experience managing and growing engineering teams, including performance management and career development planning.
• Ability to define technical vision, establish engineering standards, and align team deliverables with organisational goals.
• Strong stakeholder management skills, including handling escalations and influencing at senior levels.
• Experience driving technical roadmap planning across multi-disciplinary teams.

Communication & Collaboration:

• Clear, confident written and verbal communication skills.
• Comfortable engaging with customers and senior stakeholders to articulate technical decisions, solution architecture, and delivery strategy.
• Effective leader in design reviews, sprint planning, technical discussions, and delivery execution.

Delivery & Process:

• Experience defining and improving engineering processes, documentation standards, and delivery governance.
• Strong track record of authoring and reviewing design documents, functional requirements, test strategies, and deployment guides.
• Experienced in Agile/Scrum environments with a focus on predictable, high-quality delivery.
• Willingness to work in US shift hours (5 PM – 2 AM IST).

You Will Have an Advantage If You Also Have:

• Hands-on experience with NICE CXone products or other cloud-based contact centre platforms.
• Experience with enterprise conversational AI platforms such as NICE CXone, Kore.ai, Amelia, Dialogflow, or similar.
• Exposure to Generative AI tools, LLM fine-tuning, or RAG-based architectures.

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: 10786

Reporting Into: Director , Engineering 

Role Type: People Management

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