Our partner is looking for a Forward Deployed Agile Software Engineer based in Spain. Join a forward-thinking engineering environment where software development, artificial intelligence, and product innovation come together to solve complex business challenges. In this role, you will work directly with clients to transform ambiguous needs into practical, production-ready digital solutions. You will design and build AI-powered applications, autonomous agents, intelligent workflows, and full-stack software tailored to real-world business requirements. Collaborating with multidisciplinary teams, you will move seamlessly from technical discovery and rapid prototyping to deployment and continuous improvement. Partner with clients and internal teams to understand business objectives, operational workflows, technical environments, data sources, and constraints. AI application and software development: Design, develop, and deploy AI-enabled applications, agentic workflows, APIs, developer tools, data pipelines, and full-stack products that address real business needs. Build the infrastructure surrounding AI models, including prompts, tools, context management, memory, permissions, runtime controls, observability, and feedback mechanisms required for reliable production performance. Develop and refine agent loops that support planning, tool selection, execution, observation, reflection, recovery, and termination. Model complex workflows using graphs, state machines, and orchestration patterns that coordinate models, systems, data, and human approvals. Evaluation and quality assurance: Create evaluation frameworks and testing strategies to measure task completion, accuracy, reliability, safety, latency, cost, and user value. Use representative datasets, regression testing, human review,



and production feedback to continuously improve system performance. Connect AI solutions to client systems, enterprise data sources, cloud platforms, APIs, databases, and third?Instrument applications to capture traces, intermediate states, performance metrics, and failures. Apply strong software engineering practices across automated testing, documentation, security, version control, observability, and continuous integration and delivery. Work closely with product managers, designers, engineers, data specialists, security teams, and client stakeholders. Develop reusable components, technical patterns, and implementation insights that strengthen future projects. Professional software engineering

experience:
grade software, ideally including AI?powered applications, autonomous agents, or agentic systems. Strong skills in Python, TypeScript, or another programming language commonly used for AI applications, platforms, and developer tooling. Practical understanding of how to design the infrastructure, context, tools, permissions, controls, and feedback mechanisms that enable AI agents to operate reliably in production. Experience building or working with agent loops involving planning, tool selection, execution, observation, reflection, recovery, and termination. step workflows coordinating agents, tools, data, and human approvals. AI evaluation and testing: graded evaluations, human review,



and production monitoring. offs affecting quality, reliability, latency, and cost. Experience instrumenting AI systems to trace decisions, inspect intermediate states, measure quality, and diagnose failures. Strong understanding of APIs, distributed systems, databases, cloud infrastructure, and modern software development practices. Ability to quickly understand unfamiliar technologies, business domains, and existing systems, then turn ambiguous customer problems into tested prototypes and production?Ability to balance model capabilities, reliability, security, latency, cost, maintainability, and user experience when making technical decisions. Experience with agent frameworks, workflow engines, coding agents, or custom model?Experience building tool interfaces, execution sandboxes, permission models, and human?in?the?loop controls for autonomous or semi?Experience evaluating AI systems using golden datasets, simulators, adversarial testing, online experiments, and production feedback. Familiarity with AI observability tools and practices, including execution traces, token and cost analysis, latency monitoring, failure classification, and quality dashboards. Understanding of AI security risks, including prompt injection, data leakage, excessive agency, insecure tool use, and supply?Experience with cloud platforms such as AWS, Microsoft Azure, or Google Cloud, as well as containers, Kubernetes, infrastructure as code, and CI/CD tooling. source AI infrastructure, evaluation tools, agent frameworks, or related projects. world software and production systems rather than limiting your work to recommendations or presentations. Explore AI-powered applications, agentic systems, harness engineering, mo

📌 Forward Deployed Agile Software Engineer (España)
🏢 Jobgether
📍 España