Senior Software Engineer, Agents
New
J
JobgetherArtificial Intelligence
CanadaFull-TimeSenior
Salary not disclosed
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Job Details
- Required Skills
- PythonSQLTypeScriptRESTful APIsPrompt EngineeringLLMDistributed Systems
Requirements
- Strong experience building and deploying production-grade software systems.
- Experience working with integrations, APIs, endpoints, and distributed systems.
- Ability to understand complex customer workflows and translate business needs into technical solutions.
- Strong knowledge of integration patterns, authentication methods, error handling, and API reliability practices.
- Experience designing structured prompts, instructions, or workflows for large language models and AI systems.
- Ability to evaluate and improve AI-generated outputs through testing, iteration, and quality measurement.
- Comfortable working directly with customers, building trust, gathering requirements, and communicating technical concepts clearly.
- Strong problem-solving skills with the ability to navigate unclear requirements and complex technical challenges.
- Experience with programming languages such as TypeScript, Python, SQL, or similar technologies.
- Familiarity with conversational AI, voice technology, contact center platforms, or LLM-based applications.
- Ability to work independently in a remote environment while collaborating effectively with distributed teams.
Responsibilities
- Own the full lifecycle of AI agents, including discovery, design, development, testing, deployment, and ongoing optimization.
- Collaborate directly with customers to understand workflows, business goals, and operational challenges, translating them into effective AI agent solutions.
- Define agent scope, conversation behavior, escalation paths, and success criteria based on customer requirements.
- Design and write agent instructions, prompts, conversation flows, and behavioral logic to create effective customer interactions.
- Build and maintain integrations between AI agents and customer systems, including APIs, CRM platforms, ticketing tools, and internal services.
- Create and maintain evaluation frameworks, test scenarios, and quality benchmarks to improve agent performance.
- Optimize AI agents for production readiness by improving reliability, latency, cost efficiency, and user experience.
- Monitor live deployments and troubleshoot issues quickly to maintain customer satisfaction.
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