Convo & Agentic AI Developer -Associate 2

The Opportunity

Join our Acceleration Center India and help shape the future of business for our diverse client portfolio across geographies and jurisdictions. You’ll work at the heart of global teams across Advisory, Assurance, Tax and Business Services—solving real client challenges through connected collaboration. We’ll help you grow your skills so you can go further. With hands-on learning, cutting-edge tools and an inclusive culture, this is your opportunity to do inspiring work that makes a difference—every day.

As a Convo & Agentic AI Developer - Associate 2, you will engage in designing and implementing AI systems that transform raw data into actionable insights, driving business growth and informed decision-making. Within our Technology Consulting practice, you will apply your skills in data, algorithms, and software engineering to build scalable AI and Machine Learning solutions. As an Associate, you will focus on learning and contributing to client projects, developing your skills and knowledge to deliver quality work.

You will be expected to adapt to diverse client needs and team dynamics, using these experiences as opportunities for growth.

In this role at PwC Acceleration Center India, you will take ownership of your development, actively seeking feedback and applying a learning mindset. You will gather information from various sources to analyze facts and discern patterns, building commercial awareness and understanding how the business operates. By upholding professional and technical standards, you will contribute to the success of your team and clients, while building a personal brand that opens doors to future opportunities.

Responsibilities

Design, build, and maintain intents, entities, dialog flows, and NLU models for voicebots/chatbots on one or more CCaaS platforms (e.g., NICE CXone, Genesys Cloud, Amazon Connect, Five9, Avaya, Twilio Flex).

Configure and tune IVR call flows, DTMF/ASR grammar, barge-in, and voice biometrics settings for optimal containment and CSAT.

Write, test, and iterate conversation scripts/prompts, handling edge cases, disambiguation, and graceful fallback/escalation to human agents.

Monitor bot performance (containment rate, deflection, intent accuracy, CSAT) and continuously retrain/tune NLU models using production utterances.

Design and build LLM-powered agents capable of multi-step reasoning, tool/API invocation, and task completion (e.g., order status lookup, refunds, appointment scheduling) within the contact center workflow.

Implement RAG (retrieval-augmented generation) pipelines connecting agents to knowledge bases, CRM, ticketing, and backend systems for grounded, accurate responses.

Orchestrate multi-agent workflows (e.g., using LangChain, LangGraph, Semantic Kernel, or platform-native agent builders) including handoffs between specialized agents and human-in-the-loop checkpoints.

Apply prompt engineering, guardrails, and evaluation frameworks to ensure agent responses are accurate, safe, and on-brand.

Collaborate with solution architects, QA, and platform teams to deploy, test, and support bots/agents in production environments.

Document flows, prompts, agent logic, and integration architecture for handover, audits, and knowledge continuity.

Design, develop, and maintain end-to-end applications supporting contact center operations, spanning front end interfaces, backend services, and data layers

Implement backend business logic, orchestration layers, and serverless functions supporting contact center workflows

Assist in solution design and architecture for chatbot, voicebot, and IVR journeys across multiple CCaaS platforms.

Own end-to-end bot lifecycle: Conversation design, NLU/NLP model development, integration, testing, deployment, and post-go-live optimization.

Integrate conversational solutions with CRM, ticketing, telephony (SIP/IVR), and backend enterprise systems using APIs, middleware, and webhooks.

Define and enforce best practices, reusable components, and design standards across projects.

Implement authentication, authorization, and secure data exchange patterns across application tiers

Analyze application and system performance and proactively optimize scalability, reliability, and maintainability

Collaborate with solution architects, product owners, and clients to translate business requirements into technical designs.

Troubleshoot production issues and drive root-cause analysis for bot performance degradation.

Support deployment, environment configuration, and release activities in partnership with DevOps teams

Collaborate closely with product owners, architects, designers, and cross-functional development teams to ensure successful delivery of solutions

Participate in architectural discussions, solution design reviews, code reviews, and best practice implementations

Manage defects through triage, root cause analysis, and resolution within agreed quality standards

Requirements

Technical Skills:

Hands-on experience with at least one CCaaS platform: NICE CXone, Genesys Cloud/PureCloud, Amazon Connect, Five9, Avaya, Twilio Flex, or similar.

Practical experience building chatbots/voicebots using NLU engines such as Google Dialogflow, Amazon Lex, Microsoft Bot Framework/CLU, IBM Watson Assistant, or Nuance Mix.

Working knowledge of LLMs and agentic frameworks (OpenAI/Anthropic APIs, LangChain, LangGraph, Semantic Kernel, or equivalent) and prompt engineering fundamentals.

Understanding of RAG architecture, vector databases (Pinecone, Weaviate, FAISS), and basic API/webhook integration (REST, JSON).

Familiarity with a scripting/programming language (Python, JavaScript/Node.js) for custom logic, integrations, or agent tooling.

Strong analytical skills to interpret conversation logs, transcripts, and bot analytics dashboards to identify improvement areas.

Clear written and verbal communication for documenting flows and collaborating with cross-functional teams.

Proven track record independently owning at least one end-to-end conversational or agentic AI deployment from design through go-live.

Experience defining evaluation metrics/test suites for LLM agent quality (accuracy, hallucination rate, task success rate).

Prior experience mentoring junior engineers or reviewing others' bot builds/prompt designs.

Proficiency in software development using Java, JavaScript, Python, or similar programming languages

Hands-on experience in front end programming using JavaScript, HTML, CSS, and modern frameworks such as React or Angular

Strong experience in API development and REST API integration, including authentication mechanisms and cloud-based services

Experience designing and building microservices and event-driven architecture

Strong grounding in solution design, DevOps collaboration, and defect management practices

Experience with speech analytics, sentiment analysis, or real-time agent-assist tools.

Knowledge of telephony protocols (SIP, WebRTC) and voice biometrics.

Exposure to MLOps/LLMOps practices for monitoring and continuously improving deployed models/agents.

Relevant certifications (e.g., Genesys Cloud Certified, NICE CXone, AWS Certified – Machine Learning/Connect, Google Dialogflow).

Platforms & Technologies

CCaaS Platforms: NICE CXone, Genesys Cloud, Amazon Connect, Five9, Avaya, Twilio Flex

NLU/Bot Builders: Dialogflow CX/ES, Amazon Lex, Microsoft Bot Framework, Watson Assistant, Nuance Mix

Agentic/LLM Frameworks: OpenAI, Anthropic (Claude), LangChain, LangGraph, Semantic Kernel, AutoGen

Integration & Data: REST/webhooks, Salesforce, ServiceNow, Zendesk, vector DBs (Pinecone/Weaviate/FAISS)

Languages: Python, JavaScript/Node.js, JSON/YAML

Cloud & serverless: AWS (Connect, Lambda, Lex, AWS AI Agents), Azure, Google Cloud Platform (GCP)

CCaaS platforms: Amazon Connect, NICE CXone Mpower, Genesys CX

AI & Gen AI: Amazon Bedrock, Google Vertex AI, OpenAI, Kore.ai, Google Dialogflow CX

Languages & data: Python, SQL, Power BI, Databricks

Version control: GitHub

Methodologies & Tools

Experience working in SAFE Agile / Agile / Scrum development environments

Familiarity with CI/CD pipelines, DevOps practices, and cloud-native development is a plus What You Must Have

B. Engg./ B. Tech., M. Engg./ M. Tech. from a premier Technical/ Engineering School

2 - 5 years of experience

Oral and written proficiency in English required

What Sets You Apart

Preference for at least one of the following fields of study: Management Information Systems, Computer and Information Science, Systems Engineering, Mathematics, Engineering, Electrical Engineering, Chemical Engineering, Industrial Engineering, Mathematics, Statistics, or Mathematical Statistics, Data Processing/Analytics/Science, Artificial Intelligence and Robotics

At least one of the following: Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS, Google Cloud, Microsoft Azure, Databricks, Snowflake, or related data and AI credentials

Demonstrating proficiency in AI implementation and machine learning libraries

Utilizing programming languages such as Python, Java, and C++

Engaging in complex data analysis and data modeling techniques

Applying knowledge of natural language processing and sentiment analysis

Excelling in teamwork and active listening within client support environments

Employment type: Full-time

Industries: Professional Services