Role overview

Responsibilities:

Undertakes the development, configuration, implementation and support of Artificial Intelligence (AI), Generative AI and Conversational AI solutions based on business requirements, architecture standards, security policies, best practices and project deliverables.
Designs, develops and supports AI-powered conversational IVR solutions, virtual assistants, voicebots, AI agents and self-service capabilities utilizing Amazon Connect Customer AI Agents, Amazon Bedrock, Amazon Lex and related technologies.
Develops and maintains integrations between AI solutions, contact centre platforms, enterprise applications, knowledge repositories, APIs, workflow systems and cloud services.
Designs, develops and optimizes prompts, prompt templates, orchestration logic, retrieval mechanisms and AI guardrails to ensure secure, accurate and effective AI interactions.
Develops and supports AI Agents leveraging Large Language Models (LLMs), Retrieval Augmented Generation (RAG), Model Context Protocol (MCP) servers, tool-calling frameworks and enterprise knowledge repositories.
Configures and develops Amazon Lex bots including intents, slots, utterances, fulfillment logic, conversational flows and escalation mechanisms.
Works closely with architects, business analysts, contact centre teams and stakeholders to implement scalable, secure and reliable AI solutions.
Develops technical specifications, implementation documentation, deployment procedures and operational support materials.
Participates in testing, troubleshooting, deployment and ongoing optimization of AI-powered contact centre solutions.
Ensures solutions comply with organizational standards for security, privacy, accessibility and Responsible AI.

General Skills:

Knowledge of Artificial Intelligence (AI), Generative AI, Machine Learning (ML), Large Language Models (LLMs), Agentic AI and Conversational AI technologies.
Knowledge of Retrieval Augmented Generation (RAG), prompt engineering, vector databases and semantic search technologies.
Knowledge of Amazon Connect, Amazon Bedrock, Amazon Lex and AWS cloud services.
Knowledge of MCP (Model Context Protocol) concepts, tool integration patterns and AI agent orchestration.
Knowledge of cloud computing technologies, APIs, microservices and event-driven architectures.
Ability to gather technical requirements and translate them into scalable AI solutions.
Ability to develop technical designs, implementation specifications and support documentation.
Knowledge of technology trends, emerging AI capabilities and industry best practices.
Excellent analytical, problem-solving and troubleshooting skills.
Excellent verbal and written communication skills, interpersonal skills and teamwork skills.
A team player with a track record for meeting deadlines.

Requirements

Experience and Skill Set Requirements:

Must Haves:

5+ years of experience developing Artificial Intelligence and Machine Learning solutions.
Hands-on experience implementing Generative AI and Large Language Model (LLM) solutions in enterprise environments.
5+ years of experience implementing contact centre solutions utilizing Amazon Connect.
Experience configuring and developing Amazon Connect Customer AI Agents.
Extensive experience designing, developing and implementing Amazon Connect cloud-based contact centre solutions.
Experience integrating Amazon Bedrock services with Amazon Connect solutions.
Experience designing, developing and optimizing prompts for conversational AI, virtual assistants and AI agents.
Experience with AWS services including Amazon Connect, Amazon Bedrock, Amazon Lex, AWS Lambda, API Gateway, Amazon DynamoDB, Amazon S3, CloudWatch, EventBridge and IAM.
Knowledge of Azure OpenAI, Azure AI Services, Azure AI Foundry, Google Vertex AI, Gemini and equivalent AI platforms.
Strong experience with Python development.
Experience with JavaScript, Node.js and related technologies.
5+ years of experience implementing conversational AI, IVR or contact centre solutions.

Nice to have:

Prior OPS or Public sector exp.

Skill Set Requirements:

Technical Skills:

AI Engineering & Generative AI:

5+ years of experience developing Artificial Intelligence and Machine Learning solutions.
Hands-on experience implementing Generative AI and Large Language Model (LLM) solutions in enterprise environments.
Experience building and supporting AI Agents utilizing foundation models and agent orchestration frameworks.
Experience implementing Retrieval Augmented Generation (RAG) architectures utilizing enterprise knowledge repositories.
Experience working with foundation models including Anthropic Claude, OpenAI GPT, Google Gemini, Meta Llama or equivalent technologies.
Experience evaluating and selecting AI technologies, foundation models and AI services based on business requirements.
Experience designing and implementing AI-powered customer self-service and conversational solutions.
Experience with AI model monitoring, evaluation, optimization and performance tuning.
Understanding of Responsible AI practices, AI safety controls and governance principles.

Amazon Connect, Bedrock & Lex Development:

5+ years of experience implementing contact centre solutions utilizing Amazon Connect.
Experience configuring and developing Amazon Connect Customer AI Agents.
Extensive experience designing, developing and implementing Amazon Connect cloud-based contact centre solutions.
Experience integrating Amazon Bedrock services with Amazon Connect solutions.
Experience developing conversational IVR, virtual assistants and voice-enabled self-service capabilities.
Experience developing and supporting Amazon Lex bots including intents, slots, utterances, fulfillment logic and conversational workflows.
Strong knowledge of Contact Lens, Contact Trace Records (CTR), reporting, dashboards, analytics and operational metrics.
Experience developing contact flows, routing logic, customer journeys and escalation mechanisms.
Knowledge of intelligent routing, intent recognition and conversational design concepts.

Prompt Engineering, Guardrails & MCP:

Experience designing, developing and optimizing prompts for conversational AI, virtual assistants and AI agents.
Experience creating prompt engineering frameworks, templates and reusable design patterns.
Experience implementing AI guardrails including content filtering, safety controls, grounding strategies, response validation and hallucination mitigation.
Experience developing and supporting Model Context Protocol (MCP) server integrations.
Experience implementing AI agent tool-calling, function-calling and orchestration capabilities.
Experience integrating AI agents with enterprise tools, APIs and business applications.
Experience evaluating AI response quality, prompt effectiveness and conversational outcomes.
Experience implementing testing and monitoring frameworks for conversational AI solutions.

AWS, Cloud & Integration Technologies:

Experience with AWS services including Amazon Connect, Amazon Bedrock, Amazon Lex, AWS Lambda, API Gateway, Amazon DynamoDB, Amazon S3, CloudWatch, EventBridge and IAM.
Experience developing REST APIs, web services and enterprise integrations.
Experience with serverless application development.
Experience developing microservices and event-driven solutions.
Experience implementing CI/CD pipelines and DevOps practices.
Experience with Infrastructure as Code and cloud automation tools.
Knowledge of AWS SageMaker for machine learning model development, deployment and monitoring.
Knowledge of Azure OpenAI, Azure AI Services, Azure AI Foundry, Google Vertex AI, Gemini and equivalent AI platforms.

Development Technologies:

Strong experience with Python development.
Experience with JavaScript, Node.js and related technologies.
Experience with SQL and NoSQL databases.
Experience utilizing Git, GitLab, Jenkins or similar DevOps tools.
Experience troubleshooting and supporting cloud-native applications.
Experience implementing secure software development practices.

Core Skills and Experience:

8+ years of experience with:

Software development and application integration.
Developing and maintaining technical designs, specifications and documentation.
Designing and implementing APIs and enterprise integrations.
Agile software delivery methodologies.
Troubleshooting and root cause analysis.
Unit testing, integration testing and performance testing.
Cloud-native application development.
Supporting production environments and operational processes.
Working closely with business stakeholders and technical teams.
Evaluating new technology alternatives and vendor products.
Providing recommendations for technical improvements and solution optimization.
Designing, maintaining and managing automation solutions and operational processes.

AI / Contact Centre Domain Experience:

5+ years of experience implementing conversational AI, IVR or contact centre solutions.
Experience developing AI-driven customer service and citizen-facing solutions.
Experience implementing AI Agents, virtual assistants and conversational self-service solutions.
Experience utilizing Amazon Connect Customer AI Agents in enterprise environments.
Experience implementing Retrieval Augmented Generation (RAG) and enterprise knowledge retrieval capabilities.
Experience with speech analytics, sentiment analysis and customer experience optimization technologies.
Knowledge of contact centre metrics, reporting and operational analytics.
Experience utilizing Contact Lens and CTR reporting to analyze customer interactions and improve outcomes.
Experience with large, complex IT projects.

General Skills:

Proven technical leadership skills with ability to identify areas for improvement and recommend solutions.
Exceptional analytical, problem-solving and decision-making skills.
Demonstrated strong troubleshooting and critical-thinking experience.
Demonstrated strong interpersonal, verbal and written communication and presentation skills.
Ability to work independently and collaboratively within multidisciplinary teams.
Strong organizational, planning and time management skills.
Demonstrated commitment to innovation, continuous improvement and quality service delivery.
Ability to learn and adapt to emerging AI technologies and industry trends.

Public Sector Experience:

Knowledge of Public Sector Enterprise Architecture artifacts (or similar), processes and practices.
Experience producing technical documentation that complies with industry-standard practices.
Knowledge and experience implementing solutions within government or highly regulated environments.
Experience adopting and adhering to Public Sector Unified I&IT Project Methodology, Public Sector Enterprise Architecture and Public Sector Standard Systems Development Methodologies.
Experience supporting large-scale public sector digital transformation initiatives.