Sr. Associate, Digital Agent Developer

Description

The company is a Fortune 10 healthcare business known for insights, products and services that make good care easier to reach and more affordable.

The Contact Center AI team uses AI-driven digital agents to improve the customer journey across voice, chat and email for the company's businesses.

The team builds and runs digital agents on Sierra Agent OS and connects them to the contact center and nearby enterprise systems. This is where new agents and capabilities are created and existing agents are improved.

Sierra is new to the team, so prior Sierra experience is a plus, not a requirement, and you will be trained on it. What matters more is hands-on experience building AI agents, including prompts, tool calling, handoffs, testing, and spotting when an agent gets something wrong.

You will work alongside platform engineers, solution architects and business stakeholders to deliver scalable, secure and effective AI experiences.

Responsibilities

• Build, configure and tune conversational AI agents on Sierra Agent OS.
• Create reusable reference models and design patterns that fit several business use cases.
• Shape agent experiences across voice, chat and email.
• Review conversation data and performance metrics to improve accuracy, containment and customer outcomes.
• Write and improve prompts, workflows, decision logic and handoffs to human agents.
• Work with platform engineers and solution architects on how multiple LLMs are orchestrated.
• Run simulations and regression tests before each release. Review production conversations where the agent fell short, find the root cause and fix it.
• Help with testing, deployment, monitoring and ongoing improvement of agent solutions.
• Work with integration and platform teams on the APIs and tools agents call, such as account lookup, order status, case creation and appointment scheduling, including how agents should respond when those calls fail.
• Keep agent documentation, test cases and support runbooks current for the service desk and L3 support teams.
• Follow enterprise security, compliance, documentation and governance standards.

Requirements

• At least 2 years building AI agents or conversational AI such as LLM assistants, chatbots or voicebots, or AI/ML or software work with hands-on agent experience.
• A bachelor's degree in a technical field such as computer science, engineering, IT or data science, or equivalent experience.
• Hands-on experience designing, building or tuning LLM-based agents or digital assistants, including prompts, tool and function calling, workflows, guardrails and handoff to a human.
• Hands-on experience with prompt engineering, conversational design, intent modeling or Natural Language Understanding (NLU).
• Working knowledge of agentic patterns: multi-step tool use, retrieval-augmented generation (RAG), agent evaluation and testing, and how agents fail in production. This can come from any agent platform.
• Experience analyzing data to improve AI performance and user outcomes.
• Knowledge of APIs, JSON and modern development practice, and the ability to read API responses, logs and conversation transcripts to work out why an agent behaved as it did.
• Familiarity with CI/CD pipelines, version control and testing methods.
• Strong problem-solving, communication and cross-functional collaboration skills.
• Preferred: experience with multi-agent systems, agent frameworks or SDKs (e.g., LangGraph, OpenAI Agents SDK, Bedrock Agents, Vertex Agent Builder), or MCP-based tool integration.
• Preferred: hands-on Sierra Agent OS experience, or work on other agent platforms such as Salesforce Agentforce, Google CCAI/Dialogflow, Amazon Lex/Connect, Kore.ai or Microsoft Copilot Studio.
• Preferred: hands-on work with voice AI, chatbots, virtual assistants or customer-service automation.
• Preferred: knowledge of multi-LLM routing, orchestration, RAG or AI evaluation frameworks.
• Preferred: experience in healthcare, regulated industries or enterprise-scale environments.
• Preferred: exposure to analytics and monitoring tools for conversational AI performance.
• Preferred: experience with simulation-based or automated testing of conversational agents (e.g., Tosca or custom test harnesses).
• Preferred: familiarity with systems a contact center agent typically integrates with, such as Five9 or another CCaaS platform, Salesforce Service Cloud, SAP or MuleSoft APIs.
• Preferred: experience collaborating with product, architecture, platform engineering and business teams.
• Preferred: familiarity with cloud-native application development and integration patterns.

Conditions

The company is an equal opportunity employer.

Benefits

• Base pay range: $66,200 - $88,300.
• Pay depends on performance, experience and skills, equity, regular job market reviews and geographic market, and always complies with applicable regulations.
• An annual bonus or long-term incentive opportunities may be offered in addition to base pay.
• Compensation is part of the company's Total Rewards package.