Forward Deployed Engineer

About the role

Span is looking for a Forward Deployed Engineer to lead complex customer implementations, particularly in high-stakes environments where the path forward may not always be clear. You will work directly with engineering leaders at top-tier organizations to understand their unique workflows, identify their challenges, and develop tailored, impactful solutions. Your role will involve embedding with customer teams to deliver full-stack solutions that improve developer productivity and organizational clarity, ensuring the platform creates measurable value in production environments. You will serve as the technical bridge between our product and customer needs, translating field learnings into product improvements and reusable deployment patterns that benefit the entire customer base. Success in this role involves owning customer outcomes from initial engagement through stable production adoption, balancing speed with quality, technical depth with strategic thinking, and hands-on building with cross-functional collaboration.

Key facts

What you'll do

• Lead the technical deployment of multiple customer projects, guiding them from initial prototypes to full-scale production implementations.
• Embed with customer engineering teams to deeply understand their workflows, challenges, and goals.
• Develop customized full-stack solutions that address specific customer problems, utilizing TypeScript, Python, and data pipeline technologies.
• Make pragmatic trade-offs between speed and quality, ensuring that solutions are robust, scalable, and production-ready.
• Write high-quality, maintainable code across the stack, including backend, frontend, and data pipelines.
• Translate customer feedback and deployment experiences into actionable product requirements and reusable patterns.
• Collaborate with internal teams to influence and prioritize product roadmap features based on deployment insights.
• Integrate AI models, data pipelines, and other complex systems into customer environments, ensuring seamless operation.
• Maintain clear, ongoing communication with stakeholders, including technical teams and non-technical leadership, to manage expectations and provide updates.
• Document deployment processes, best practices, and reusable patterns to facilitate scaling and knowledge sharing.
• Support customers post-deployment by troubleshooting issues, optimizing performance, and ensuring ongoing platform stability.
• Act as the primary technical contact during onboarding, troubleshooting, and scaling phases.
• Advocate for customer needs internally to improve platform features, deployment strategies, and overall product quality.
• Work in a fast-paced environment, balancing multiple deployments and priorities while maintaining attention to detail.
• Collaborate with cross-functional teams including customer success, solutions, engineering, and product management.
• Contribute to the development of internal tools and processes that improve deployment efficiency and quality.
• Stay informed about the latest developments in AI, data pipelines, and cloud infrastructure to bring innovative solutions to customers.
• Participate in technical reviews, code reviews, and knowledge sharing sessions to foster team growth.
• Ensure compliance with security standards and best practices, especially when working with sensitive data or regulated environments.
• Be proactive in identifying potential issues or bottlenecks in customer deployments and addressing them promptly.
• Maintain a customer-centric mindset, ensuring solutions align with customer goals and deliver measurable impact.
• Engage in continuous learning to deepen expertise in relevant technologies and industry trends.
• Contribute to the company's mission of helping engineering organizations leverage AI effectively and efficiently.

Requirements

• A minimum of 3 years of engineering experience building full-stack products or complex integrations in fast-moving environments.
• Proven ability to write production-quality code in TypeScript/JavaScript and Python.
• Hands-on experience working with data pipelines, ETL processes, and integrating Large Language Models into workflows or products.
• Strong understanding of deploying solutions on cloud platforms, particularly AWS.
• Experience with container orchestration tools such as Kubernetes is highly desirable.
• Demonstrated ownership of customer outcomes from initial contact through to stable deployment and ongoing support.
• Excellent communication skills in English, both written and verbal, to collaborate effectively with US-based customers and internal teams.
• Ability to work effectively in ambiguous situations, adapt to changing priorities, and solve complex problems.
• Experience working in a startup environment or fast-paced organization is a plus.
• Familiarity with data pipeline tools such as Airbyte, Dagster, and Kafka is advantageous.
• Knowledge of AI and machine learning workflows, especially Large Language Models, is beneficial.
• Ability to balance technical depth with strategic thinking and cross-team collaboration.
• Strong problem-solving skills, attention to detail, and a customer-focused mindset.
• Experience with front-end frameworks like React and back-end frameworks like NestJS is a plus.
• Prior experience in solutions engineering, customer success, or technical consulting roles is beneficial.
• Willingness to work on-site in Buenos Aires, Argentina, and engage directly with customers and internal teams.

Nice to have

• Experience with Kubernetes, FluxCD, or similar deployment and orchestration tools.
• Familiarity with data integration tools such as Airbyte, Dagster, and Kafka.
• Background working with AI models, especially Large Language Models.
• Prior experience working in a Series A startup environment.
• Knowledge of ITAR regulations or working with sensitive data environments.
• Experience with front-end frameworks such as React and back-end frameworks like NestJS.
• Ability to troubleshoot complex deployment issues in cloud environments.
• Familiarity with CI/CD pipelines and automation tools.
• Experience working with cross-functional teams in a customer-facing technical role.
• Knowledge of security best practices for cloud deployments and data handling.

Skills & tools

• TypeScript, JavaScript, Python
• React, NestJS
• AWS, Kubernetes, FluxCD
• Postgres, Redis
• Airbyte, Dagster, Kafka
• Data pipelines, ETL processes
• Large Language Model integration
• Cloud deployment and orchestration
• Customer-centric problem solving
• Cross-functional collaboration
• Clear and effective communication in English

Practical notes

• This is an on-site role based in Buenos Aires, Argentina.
• The position involves direct engagement with customers, requiring travel and on-site presence.
• Candidates should be comfortable working closely with international teams and clients.
• Prior experience with cloud infrastructure, data pipelines, and deployment automation will be highly valuable.
• The company is a Series A startup, emphasizing rapid development, impactful solutions, and a collaborative environment.
• Candidates should be prepared to handle complex technical challenges and deliver scalable, reliable solutions.
• The role offers an opportunity to shape how engineering organizations adopt and leverage AI effectively.
• The environment encourages continuous learning, innovation, and ownership of customer success.
• The company values diversity, inclusion, and a customer-first mindset.
• Candidates should be proactive, adaptable, and eager to contribute to a fast-moving, high-impact team.