Agentic Engineer
Z
ZealAI software consulting
Remote (Peru); available across our primary LATAM hub in Peru.Full-Time
Salary not disclosed
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Job Details
- Required Skills
- AWSPythonJavaAzureCI/CD
Requirements
- Hands-on experience designing and shipping production agent systems involving tool and function calling, multi-step workflows, orchestration, task decomposition, or multi-agent architectures.
- Ability to explain agent-system architectural decisions, failures, and lessons learned.
- Real-world experience evaluating agent behavior and measuring system failures.
- Experience building evaluation harnesses, guardrails, grounding checks, and human-in-the-loop controls.
- Deep hands-on experience with either Azure or AWS and related AI and infrastructure services.
- Strong proficiency in Python or Java, API design, containers, automated testing, source control, and CI/CD.
- Machine learning knowledge to assess when traditional ML or deterministic approaches are more appropriate than an LLM.
- Experience delivering software within large organizations and working with role-based access, data isolation, security reviews, compliance, change control, and production governance.
- Experience with traceability, state and memory management, model routing, latency and cost visibility, retries, and idempotency for production agent systems.
- Strong verbal and written communication skills, including explaining complex AI systems, architectural decisions, risks, and tradeoffs to technical and non-technical stakeholders.
- Strong technical judgment, including recognizing when an agentic solution adds unnecessary complexity.
Responsibilities
- Work with clients to understand business problems and translate them into scalable, production-ready agentic AI solutions.
- Design and implement multi-step agent systems, including orchestration, tool and function calling, task decomposition, and multi-agent coordination where appropriate.
- Integrate agents with enterprise systems by exposing APIs as tools, implementing MCP servers, and developing structured tool contracts.
- Build evaluation frameworks, guardrails, grounding and citation checks, and human-in-the-loop workflows.
- Instrument agent systems for traceability and observability, including actions, model behavior, token and cost usage, latency, and performance.
- Design and maintain state and memory for long-running workflows, and implement model routing, retries, and idempotency.
- Build and deploy AI solutions using Azure or AWS cloud platforms and services.
- Apply software engineering practices using Python or Java, APIs, containers, source control, automated testing, and CI/CD.
- Work with client engineering and security teams on architecture reviews, threat modeling, security reviews, audits, and enterprise delivery requirements.
- Assess when agentic architectures are appropriate versus deterministic pipelines, traditional machine learning, or other approaches.
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