Senior GenAI / LLM Engineer (AWS Connect & Conversational AI)

Job Title: Senior GenAI / LLM Engineer (AWS Connect & Conversational AI)

Experience: 6+ Years

Location: Hyderabad

Employment Type: Full-Time

About the Role

We are seeking a highly skilled Senior GenAI / LLM Engineer with expertise in Generative AI, Large Language Models (LLMs), Amazon Nova Sonic, Amazon Connect, Conversational AI, and AWS AI Services. In this role, you will design and build intelligent, AI-powered customer engagement solutions that leverage voice, chat, and agent-assist capabilities to deliver exceptional customer experiences.

The ideal candidate should possess hands-on experience in AWS Connect, Amazon Nova Sonic, Agent Assist, Natural Language Understanding (NLU), conversational AI frameworks, and cloud-native application development. You will collaborate with architects, contact center teams, AI engineers, and cloud engineers to build scalable, secure, and intelligent contact center solutions powered by GenAI.

Key Responsibilities

Generative AI Solution Development

• Design, develop, and implement enterprise-grade Generative AI solutions using Large Language Models (LLMs).
• Build AI-powered conversational applications for voice and chat channels.
• Develop intelligent virtual assistants and AI-powered customer support solutions.
• Integrate foundation models into enterprise applications for customer engagement and workflow automation.
• Optimize GenAI applications for accuracy, latency, scalability, and cost efficiency.

Amazon Connect Development

• Design and implement cloud-based contact center solutions using Amazon Connect.
• Configure Contact Flows, Routing Profiles, Queues, Hours of Operation, and Agent Workspaces.
• Integrate Amazon Connect with enterprise applications, CRM platforms, and backend services.
• Develop custom Contact Center workflows using AWS services.
• Support deployment, monitoring, and optimization of Amazon Connect environments.

Amazon Nova Sonic Implementation

• Develop conversational voice experiences using Amazon Nova Sonic.
• Build low-latency, real-time voice applications powered by foundation models.
• Integrate Nova Sonic into customer service and contact center workflows.
• Optimize speech understanding, contextual conversations, and response generation.
• Improve multilingual and natural voice interaction capabilities.

Conversational AI & NLU

• Design and develop conversational AI applications with advanced Natural Language Understanding (NLU).
• Build intelligent intent recognition, entity extraction, and dialogue management capabilities.
• Improve conversation flow, context retention, and personalization.
• Develop AI-driven self-service and virtual assistant experiences.
• Optimize AI models for improved customer interactions.

Agent Assist Solutions

• Develop AI-powered Agent Assist capabilities to enhance contact center productivity.
• Build real-time recommendation engines for customer support agents.
• Implement automated call summarization and conversation insights.
• Provide contextual knowledge recommendations during live customer interactions.
• Enable intelligent response suggestions and workflow automation.

Large Language Model (LLM) Integration

• Integrate enterprise applications with modern LLM platforms.
• Develop Retrieval-Augmented Generation (RAG) solutions.
• Build prompt engineering frameworks for enterprise AI applications.
• Implement conversation memory and contextual reasoning.
• Fine-tune prompts to improve AI response quality.

AWS AI & Cloud Services

• Build cloud-native AI applications using AWS services.
• Integrate AI solutions with:
• Amazon Bedrock
• Amazon Connect
• Amazon Lex
• AWS Lambda
• API Gateway
• Amazon S3
• Amazon DynamoDB
• Amazon CloudWatch
• IAM
• Step Functions
• Develop scalable and serverless AI architectures.
• Optimize cloud infrastructure for AI workloads.

API & Backend Development

• Develop RESTful APIs to integrate AI services with enterprise platforms.
• Build secure backend services using Java or Python.
• Design scalable microservices for AI workflows.
• Integrate AI models with CRM, ERP, and enterprise applications.
• Ensure secure authentication and authorization mechanisms.

AI Workflow Automation

• Design AI-driven workflow automation for customer service operations.
• Automate repetitive support tasks using intelligent agents.
• Build orchestration workflows across multiple AWS services.
• Integrate AI into existing business processes.

Testing & Optimization

• Evaluate AI model performance and conversational quality.
• Perform prompt tuning and response optimization.
• Monitor model accuracy and hallucination rates.
• Conduct A/B testing for AI interactions.
• Improve latency, scalability, and cost optimization.

Monitoring & Observability

• Implement monitoring and logging for AI applications.
• Track conversation analytics and AI performance metrics.
• Build dashboards for operational monitoring.
• Monitor application health using CloudWatch and other observability tools.
• Perform root cause analysis for AI service issues.

Security & Governance

• Ensure AI solutions comply with enterprise security standards.
• Implement secure API integrations.
• Protect sensitive customer information using encryption and IAM best practices.
• Support responsible AI and governance initiatives.
• Maintain compliance with organizational policies and regulatory requirements.

Agile Collaboration

• Collaborate with Product Owners, AI Architects, Cloud Engineers, DevOps, QA, and Business stakeholders.
• Participate in Agile ceremonies including Sprint Planning, Stand-ups, Reviews, and Retrospectives.
• Mentor junior developers and contribute to AI architecture discussions.
• Stay current with emerging AI technologies and AWS innovations.

Required Qualifications

Experience

• 6+ years of experience in software development, AI engineering, or cloud application development.
• Hands-on experience with Generative AI and LLM-based applications.
• Experience implementing enterprise conversational AI solutions.
• Experience working with Amazon Connect in production environments.

Technical Skills

Generative AI

• Large Language Models (LLMs)
• Generative AI
• Prompt Engineering
• Retrieval-Augmented Generation (RAG)
• AI Agents
• Conversational AI
• Context Management
• AI Workflow Automation

Amazon Nova Sonic

• Amazon Nova Sonic
• Real-Time Voice AI
• Speech Understanding
• Voice Assistants
• Conversational Voice Applications

Amazon Connect

• Contact Flows
• Routing Profiles
• Queues
• Agent Workspace
• Contact Center Architecture
• Voice & Chat Channels
• Customer Experience Solutions

Agent AI / Agent Assist

• AI Agent Assist
• Call Summarization
• Intelligent Recommendations
• Knowledge Retrieval
• Live Agent Support
• AI-Powered Customer Assistance

Natural Language Understanding (NLU)

• Intent Recognition
• Entity Extraction
• Dialogue Management
• Contextual Conversations
• Semantic Search

AWS Services

• Amazon Connect
• Amazon Bedrock
• Amazon Lex
• AWS Lambda
• API Gateway
• Amazon S3
• DynamoDB
• IAM
• CloudWatch
• Step Functions
• SNS
• SQS

Programming Languages

• Python
• Java
• JavaScript (Preferred)

Backend Development

• REST APIs
• Spring Boot (Preferred)
• Flask / FastAPI
• Microservices Architecture
• JSON
• OAuth2
• JWT

Databases

• PostgreSQL
• DynamoDB
• Vector Databases (Preferred)
• SQL
• NoSQL

DevOps & CI/CD

• Git
• Jenkins
• GitHub Actions
• Docker
• Kubernetes (Preferred)
• Terraform (Preferred)

Monitoring

• CloudWatch
• Datadog
• Grafana
• Logging & Monitoring
• AI Performance Analytics

Preferred Qualifications

• Experience with Amazon Bedrock foundation models.
• Hands-on experience with LangChain, LangGraph, or similar AI orchestration frameworks.
• Experience with vector databases such as Pinecone, Weaviate, OpenSearch Vector Engine, or Milvus.
• Knowledge of Amazon Transcribe, Amazon Polly, and Amazon Comprehend.
• Experience with AI governance, Responsible AI, and model evaluation.
• Experience in Banking, Financial Services, Healthcare, Retail, or Customer Experience platforms.

Soft Skills

• Excellent communication and stakeholder management skills.
• Strong analytical and problem-solving abilities.
• Ability to translate business requirements into AI-driven solutions.
• Strong collaboration skills across cross-functional teams.
• Passion for innovation and continuous learning in AI technologies.
• Ability to mentor and guide junior engineers.