Digital Agent Developer

Description

The company is a Fortune 10 healthcare company that delivers insights, products, and services to make quality care more accessible and affordable.

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

The team designs, builds, and runs digital agents on Sierra Agent OS and connects them to the contact center and enterprise systems around them.

This role builds new agents and new capabilities and improves existing ones.

Hands-on Sierra experience is a plus, not a requirement, since the company will ramp you on the platform. Real experience building AI agents is required, including prompts, tool calling, handoffs, testing, and recognising when an agent is wrong.

The role reports into the Contact Center AI team and works closely with platform engineers, solution architects, and business stakeholders to deliver scalable, secure, and effective AI experiences.

Responsibilities

• Design, configure, and tune conversational AI agents in Sierra Agent OS.
• Create reusable reference models and design patterns that serve several business use cases.
• Build and improve agent experiences for voice, chat, and email.
• Review conversation data and performance metrics to raise accuracy, containment, and customer outcomes.
• Write and refine prompts, workflows, decision logic, and handoff experiences.
• Work with platform engineers and solution architects on multi-LLM orchestration.
• Support testing, deployment, monitoring, and ongoing improvement of agent solutions.
• Run simulations and regression tests before each release, then examine production conversations where the agent fell short, find the cause, and fix it.
• Work with integration and platform teams on the APIs and tools agents call, such as account lookup, order status, case creation, and appointment scheduling, and define agent behaviour when those calls fail.
• Maintain agent documentation, test cases, and the support runbooks used by the service desk and L3 support.
• Follow enterprise security, compliance, documentation, and governance standards.

Requirements

• At least 2 years building AI agents or conversational AI solutions such as LLM assistants, chatbots, or voicebots, or in AI/ML or software development with hands-on agent work.
• A bachelor's degree in Computer Science, Engineering, Information Technology, Data Science, or equivalent experience.
• Hands-on work designing, building, or tuning LLM-based agents or digital assistants, covering 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 AI patterns: multi-step tool use, retrieval (RAG), agent evaluation and testing, and how agents fail in production. This can come from any agent platform.
• Experience analysing data and using the findings to improve AI performance and user outcomes.
• Knowledge of APIs, JSON, and modern software practices, including reading API responses, logs, and transcripts to explain why an agent acted as it did.
• Familiarity with CI/CD pipelines, version control, and testing methods.
• Strong problem-solving, communication, and cross-functional collaboration skills.
• Nice to have: 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.
• Nice to have: hands-on Sierra Agent OS experience, or experience with other agent platforms such as Salesforce Agentforce, Google CCAI/Dialogflow, Amazon Lex/Connect, Kore.ai, or Microsoft Copilot Studio.
• Nice to have: hands-on work with voice AI, chatbots, virtual assistants, or customer-service automation.
• Nice to have: knowledge of multi-LLM routing, orchestration, RAG, or AI evaluation frameworks.
• Nice to have: experience in healthcare, regulated industries, or enterprise-scale environments.
• Nice to have: exposure to analytics and monitoring tools for conversational AI performance.
• Nice to have: experience with simulation-based or automated testing of conversational agents, such as Tosca or custom test harnesses.
• Nice to have: familiarity with contact center integrations such as Five9 or another CCaaS platform, Salesforce Service Cloud, SAP, or MuleSoft APIs.
• Nice to have: experience working with product, architecture, platform engineering, and business teams.
• Nice to have: familiarity with cloud-native application development and integration patterns.

Conditions

Travel is minimal and depends on business needs.

The role can be hybrid or remote, subject to business and team requirements.

You must be able to work at a computer and join virtual and in-person meetings for long periods.

Base pay ranges from $81,500 to $108,600. Pay depends on performance, experience and skills, equity, regular market reviews, and location, and always complies with applicable regulations.

Equal opportunity employer.

Benefits

• Eligible for the company's Total Rewards package, which may include an annual bonus or long-term incentive opportunities in addition to base pay.
• Benefit details are available on the company's careers site.