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, CRM systems, and knowledge bases. Lead technical delivery and stakeholder discussions, mentor developers, and ensure solutions are secure, scalable, observable, cost-optimised, and governed by responsible AI controls.

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, contact-centre domain knowledge, and a bachelor's degree in Engineering or Computer Science; a master's degree and Azure certifications are preferred.