Agentic AI Developer - Voice & Chat Automation

Agentic AI Developer - Voice & Chat Automation

Expected Outcomes in This Role -

• Voice and Chat Agentic Agents that successfully resolve the majority of customer interactions autonomously

• Measurable reduction in reliance on static IVR menus and scripted chatbot workflows

• Highly performant, scalable automation systems capable of supporting real-time interactions

• Continuous improvement in automation accuracy, completion rates, and overall user experience

Role Overview

We are seeking an experienced Agentic AI Developer to design, build, and optimize Voice and Chat Agentic Agents that handle customer interactions before they are transferred to live agents. This role focuses on creating intelligent, autonomous agents that resolve customer needs through natural voice and chat experiences, leveraging reasoning, context, and backend integrations instead of static scripts or decision trees.

The ideal candidate brings a strong technical foundation in LLMs, agent orchestration, and distributed systems, along with experience evolving traditional IVR or chatbot solutions into modern agentic AI architectures.

Key Responsibilities

Agentic AI Development

• Design and implement Voice and Chat Agentic Agents capable of multi-step reasoning, tool execution, and dynamic decision-making

• Develop agent architectures leveraging planning, tool usage, memory management, and orchestration frameworks

• Build systems that enable agents to autonomously resolve customer intents end-to-end

Voice & Chat Experience Engineering

• Engineer AI-driven voice and chat interaction layers that replace or enhance traditional IVR and scripted bots

• Implement NLU/NLP capabilities using LLMs, embeddings, and prompt orchestration

• Design flexible, context-aware interactions that dynamically adapt to user input

Backend Integration & Action Execution

• Build and maintain integrations with enterprise systems through REST/GraphQL APIs, event-driven architectures, and microservices

• Enable agents to securely perform actions including authentication, data retrieval, updates, and transactions

• Implement middleware layers to manage agent-to-system communication, retries, and error handling

Architecture & Scalability

• Design scalable, production-grade systems capable of supporting high concurrency, low latency, and real-time interactions

• Implement retrieval-augmented generation (RAG) using vector databases and knowledge stores

• Optimize system performance, caching strategies, and inference efficiency

Evaluation, Observability & Optimization

• Implement telemetry, logging, and tracing across agent interactions

• Define and monitor metrics including task completion, containment, latency, and failure modes

• Build evaluation pipelines to test prompts, workflows, and agent behaviors at scale

Safety & Control

• Implement guardrails, policy controls, and validation layers to ensure safe and compliant AI behavior

• Design fallback and escalation mechanisms when confidence or capability thresholds are not met

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, AI, or a related field (or equivalent experience)

• 4+ years of software engineering experience with strong backend development capabilities

• Hands-on experience with large language models (LLMs) and agent-based architectures

• Experience developing conversational systems for voice and/or chat interfaces

• Strong programming skills in Python, JavaScript/TypeScript, or similar languages

• Experience with:

• API design and integration (REST, GraphQL)

• Cloud platforms (Azure, AWS, or GCP)

• Microservices and distributed system design

Familiarity with:

• Prompt engineering and orchestration patterns

• Vector databases (e.g., Pinecone, Redis, Azure AI Search)

• CI/CD and DevOps practices

Preferred Qualifications

• Experience transitioning traditional IVR or chatbot systems to AI-driven agentic architectures

• Experience with speech technologies (ASR, TTS, voice streaming frameworks)

• Familiarity with agent frameworks such as Semantic Kernel, LangChain, or similar

• Experience implementing RAG pipelines and knowledge grounding

• Exposure to Salesforce ecosystem tools, including Salesforce Agentforce

• Experience designing automation for high-volume, customer-facing interactions

Key Skills

• Agentic AI design (planning, tool usage, memory, orchestration)

• Voice and chat conversational engineering

• Distributed systems and API integration

• Performance optimization and scalability

• Data-driven iteration and system tuning