Key Skills

Job Description

Job description: Role summary Design, build and deploy production-grade AI solutions on Microsoft Azure with a strong focus on voice AI and customer care transformation Lead hands-on development of conversational and agentic AI assistants that handle live customer interactions across voice, chat and digital channels Operate as the senior onsite technical anchor, working directly with client business, contact-centre and IT stakeholders Key responsibilities Design and develop GenAI and agentic AI solutions using Azure AI Foundry, Azure OpenAI and Azure AI services Build voice-enabled AI assistants using Azure AI Speech (speech-to-text, text-to-speech, custom neural voice) and real-time streaming audio pipelines Develop customer care use cases such as call deflection, intent detection, live agent assist, call summarisation, post-call analytics, QA scoring and sentiment analysis Integrate AI solutions with contact-centre platforms (Azure Communication Services, Dynamics 365 Customer Service, Genesys, Avaya, NICE, Amazon Connect or equivalent), IVR and CRM systems Implement RAG patterns over knowledge bases using Azure AI Search, embeddings and vector stores for accurate, grounded responses Build multi-agent orchestration flows with tool-calling, handoff-to-human logic and fallback handling Develop APIs, microservices and event-driven pipelines to operationalise AI workloads Define and implement evaluation, guardrails and Responsible AI controls — groundedness, content safety, PII redaction, bias and hallucination checks Own latency, scalability, security and cost optimisation for real-time voice workloads Set up CI/CD, LLMOps and observability for AI applications using Azure DevOps / GitHub Mentor developers, drive code and design reviews, and enforce engineering best practices Lead solution walkthroughs, demos and technical discussions with client stakeholders Required technical skills Azure AI Foundry — projects, agent service, model catalogue, prompt flow, evaluations and deployment Azure OpenAI — GPT model families, function/tool calling, fine-tuning, prompt engineering Azure AI Speech — real-time STT/TTS, custom speech models, custom neural voice, speaker recognition, diarisation Azure AI Search, vector databases, embeddings and hybrid retrieval Conversational AI platforms — Copilot Studio, Azure Bot Service, Language Understanding / CLU Agentic frameworks — Semantic Kernel, LangGraph, AutoGen, MCP or equivalent Strong Python; REST APIs, FastAPI, microservices, async and streaming architectures Azure platform services — Functions, App Service, AKS, API Management, Event Hub, Service Bus, Key Vault, Entra ID Azure DevOps / GitHub Actions, CI/CD, containerisation, infrastructure as code Monitoring and observability using Azure Monitor, Application Insights and AI evaluation tooling Domain and use-case experience Proven delivery of customer care / contact-centre AI use cases in production, not just PoCs Understanding of contact-centre operations — AHT, FCR, CSAT, containment rate, deflection and QA metrics Experience with omnichannel journeys spanning voice, chat, email and messaging Telecom, BFSI or large enterprise customer-service environments preferred Awareness of data privacy, call recording consent, GDPR and regulatory obligations in customer interactions Behavioural and soft skills Strong client-facing presence and the ability to run technical discussions independently onsite Clear technical communication with both business and engineering audiences Strong problem-solving, ownership and delivery focus Ability to mentor and guide distributed onshore–offshore teams Experience and qualifications 12+ years of overall experience in software / AI engineering 4+ years hands-on with AI/ML and GenAI solution development 2+ years building voice AI or conversational AI solutions for customer care Demonstrable hands-on experience with Azure AI Foundry and Azure OpenAI in production Bachelor's degree in Engineering / Computer Science; Master's preferred Azure certifications (AI-102, AZ-204 or equivalent) preferred Key deliverables / outcomes Production-ready voice and conversational AI assistants deployed on Azure Measurable improvement in containment, deflection, handling time and customer satisfaction Reusable AI components, prompt libraries and integration accelerators Secure, scalable and cost-optimised AI deployments with full observability Technical documentation covering HLD, LLD and integration approaches

Core Responsibilities

Design, build, and deploy production-grade voice, conversational, and agentic AI solutions on Azure for customer-care operations, integrating them with contact-centre platforms, IVR, CRM, and knowledge bases. Lead technical delivery and client discussions while ensuring responsible AI controls, security, scalability, observability, and measurable improvements to customer-service outcomes.

Requirements

Requires 12+ years of software or AI engineering experience, including 4+ years developing AI/ML and GenAI solutions and 2+ years building voice or conversational AI for customer care. Candidates should have production experience with Azure AI Foundry and Azure OpenAI, strong Python and Azure platform skills, client-facing leadership ability, and a bachelor's degree in Engineering or Computer Science; a master's degree and Azure certifications are preferred.