Required Skills: VOICE, CHAT, AUTOMATION, PYTHON, LLMS, LLM
Job Description
Agentic AI Developer (Voice & Chat Automation)
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 reach 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 rather than 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 systems.
Key Responsibilities
Agentic AI Development
- Design and implement Voice and Chat Agentic Agents capable of multi-step reasoning, task execution, and dynamic decision-making
- Develop agent architectures leveraging planning, tool use, memory management, and orchestration frameworks
- Build systems that support autonomous resolution of customer intents end-to-end
Voice & Chat Experience Engineering
- Engineer AI-driven voice and chat interaction layers that replace or augment traditional IVR and scripted bots
- Implement NLU/NLP capabilities using LLMs, embeddings, and prompt orchestration
- Design flexible, context-aware interactions that adapt dynamically to user input
Backend Integration & Action Execution
- Build and maintain integrations with enterprise systems using REST/GraphQL APIs, event-driven architectures, and microservices
- Enable agents to securely perform actions such as 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 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 for agent interactions
- Define and monitor metrics such as task completion, containment, latency, and failure modes
- Build evaluation pipelines for testing 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 related field (or equivalent experience)
- 3+ years of software engineering experience with strong backend development skills
- Hands-on experience with large language models (LLMs) and agent-based architectures
- Experience building conversational systems for voice and/or chat interfaces
- Experience transitioning from traditional IVR or chatbot systems to AI-driven agentic architectures
- Strong programming skills in Python, JavaScript/TypeScript, or similar
- 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 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
Success in This Role Looks Like
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Voice and Chat Agentic Agents that successfully resolve the majority of interactions autonomously
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Measurable reduction in reliance on static IVR menus and scripted chatbot flows
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Highly performant, scalable automation systems capable of handling real-time interactions
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Continuous improvement in automation accuracy, completion rates, and user experience