Software Engineer – Agentic System Development

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🕒 Outubro 29

🇺🇸 Estados Unidos – Remoto (EUA)

⏰ Tempo Integral

🟡 Pleno

🟠 Sênior

🧑‍💻 Engenheiro Full-stack

👻 Score fantasma 10%

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STARLIMS

SiteLinkedInTodas as Vagas

201 - 500 funcionários

Fundada em 1986

🍽️ Alimentos e Bebidas

📦 Logística

🏭 Manufatura

Food & Beverage • Logistics • Manufacturing

STARLIMS é um provedor líder de sistemas de gerenciamento de informações laboratoriais (LIMS) e soluções de informática, atendendo diversos setores, incluindo ciências biológicas, bens de consumo e saúde pública. Com mais de 1. 100 clientes em mais de 85 países, a STARLIMS simplifica as operações laboratoriais, aumenta a eficiência e melhora a integridade dos dados através de suas plataformas abrangentes. A empresa tem oferecido soluções inovadoras desde sua fundação em 1986, ajudando laboratórios a otimizarem seus processos de P&D e controle de qualidade.

Descrição

• Design and build the runtime for agents, including planning and execution loops, tool calling, state management, durable execution, and failure recovery • Build safe agent access to platform data and external systems • Design coordination, delegation, and handoff across agents and workflows • Make agent behavior versionable, testable, measurable, and regression-safe across releases • Build reusable primitives so new agents can be configured rather than rebuilt • Convert domain workflows from expert conversations into working agents • Ground agent decisions and outputs in authoritative enterprise data • Implement human-in-the-loop approval gates, override capture, uncertainty handling, and evidence for decisions • Use user corrections and overrides to improve agents • Build evaluation harnesses for multi-step agent behavior • Define production metrics for agent quality, reliability, latency, cost, and human intervention • Implement guardrails, fallbacks, timeouts, cost ceilings, observability, and tracing • Design safeguards against prompt injection, unsafe tool use, excessive permissions, and data leakage • Manage prompt evolution, model drift, and non-determinism across releases • Integrate agents with platform APIs and third-party enterprise systems • Build retrieval and context pipelines for reliable, permission-aware agent context • Design controlled execution paths with complete, traceable audit trails • Build and operate backend services on AWS • Own significant parts of system architecture and contribute to technical decisions • Contribute to infrastructure-as-code and deployment pipelines

🎯 Requisitos

• 6+ years of software engineering experience, including production systems • Strong understanding of LLM behavior, limitations, and failure modes, especially how errors compound across a multi-step run • Experience with LLM APIs, tool and function calling, and designing planning and execution loops • Experience evaluating and debugging non-deterministic systems • Solid backend and cloud experience (AWS or equivalent) • Proficiency in TypeScript and/or Python • Comfortable debugging across distributed and non-deterministic systems • Comfortable making explicit tradeoffs between accuracy, latency, reliability, and cost • Comfortable working in ambiguous problem spaces where the right architecture isn't obvious yet • Comfortable owning production systems end-to-end • Comfortable choosing conventional software over AI when AI isn't the right solution • Nice to have: C#, Microsoft .NET Framework • Nice to have: Tool and interop protocols such as MCP • Nice to have: Production LLM systems, including tool-using or multi-step agentic workflows beyond simple prompting and chat interfaces • Nice to have: Evaluation pipelines and metrics built specifically for agentic systems • Nice to have: Experience in regulated or domain-heavy systems (validation, audit trails, controlled change) • Nice to have: Retrieval and grounding techniques for supplying agent context • Nice to have: Workflow and durable-execution platforms (Temporal, Step Functions, n8n, etc.) • Nice to have: Containerization and orchestration (ECS, EKS, Kubernetes) • Nice to have: Infrastructure as Code (Terraform or similar)

🏖️ Benefícios

• Equal Opportunity Employer • Consideration for employment without regard to race, creed, religion, color, national or ethnic origin, citizenship, sex, sexual orientation, gender identity and expression, genetic information, veteran status, age or disability status

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