Sr. Associate, Digital Agent Developer

Description

The company is a large healthcare organisation whose work covers most parts of healthcare, offering insights, products and services that help make 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 builds and runs digital agents on Sierra Agent OS and connects them to contact center and enterprise systems. This role is where new agents and capabilities are built and existing ones are improved.

Hands-on Sierra experience is a plus but not required, and you will be trained on the platform. What is required is real experience building AI agents, including prompts, tool calling, handoffs, testing, and recognising when an agent is wrong.

You will work with platform engineers, solution architects and business stakeholders to deliver scalable, secure and effective AI-powered 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 refine agent experiences across voice, chat and email.
• Write and improve prompts, workflows, decision logic and handoff experiences.
• Analyse conversation data and performance metrics to raise accuracy, containment and customer outcomes.
• Review production conversations where the agent fell short, find the cause and fix it.
• Run simulations and regression tests before each release.
• Work with platform engineers and solution architects on multi-LLM orchestration.
• Work with integration and platform teams on the APIs agents call, such as account lookup, order status, case creation and appointment scheduling, and define agent behaviour when those calls fail.
• Support testing, deployment, monitoring and continuous improvement of agent solutions.
• Maintain agent documentation, test cases and 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.
• 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 human agents.
• Hands-on experience with prompt engineering, conversational design, intent modelling 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 insights to improve AI performance and user outcomes.
• Knowledge of APIs, JSON and modern software development practices, including reading API responses, logs and conversation transcripts to explain agent behaviour.
• 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 work with Sierra Agent OS, or 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, retrieval-augmented generation (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 used to evaluate conversational AI.
• 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, including 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

Base pay range is $99,100 - $132,100.

Pay depends on performance, experience and skills, equity, periodic market reviews and location. An annual bonus or long-term incentive may also be offered.

Equal opportunity employer.

Benefits

• Competitive compensation package as part of Total Rewards.