About The Position
We’re looking for customer-facing Forward-Deployed Engineers (FDEs) who can rapidly identify operational pain points, build practical AI-powered solutions and deploy them in real-world environments. This role sits at the intersection of Engineering, Product, Data and Customer Success. You’ll work directly with users to understand workflows, uncover the highest-impact problems and quickly deliver solutions using AI, automation, APIs, data engineering, ETL/ELT pipelines and cloud tooling. Success in this role requires strong engineering ability, data engineering fundamentals, operational problem-solving, communication skills and the ability to move from ambiguity to implementation quickly. You are not just advising on solutions - you are building and operationalising them.
Requirements
- Bachelor's or Master's degree in Computer Science, Software Engineering, Electrical Engineering or a related technical field
- 4-7 years of experience in software engineering, solutions engineering, technical consulting, data engineering or other business-facing technical roles
- Strong hands-on engineering skills with Python, APIs, infrastructure platforms and systems integrations
- Strong understanding of data engineering concepts, including data ingestion, cleaning, transformation, ETL/ELT, data validation and pipeline design
- Hands-on experience building or maintaining data pipelines for data-intensive applications
- Experience working with structured and unstructured data and transforming data from multiple sources into formats suitable for downstream applications
- Experience with SQL and relational databases, including querying, data transformation and troubleshooting data-related issues
- Experience deploying, supporting and troubleshooting production systems in enterprise environments
- Experience building integrations and automating workflows across multiple systems
- Experience working with APIs, databases, files and other data sources to build reliable data ingestion and processing workflows
- Practical experience using LLMs or GenAI APIs to create reliable workflows, automations or internal tools
- Familiarity with modern AI tooling, agent frameworks, prompt engineering and orchestration platforms
- Understanding of the data requirements and challenges involved in building AI/ML applications, including data preparation, retrieval, evaluation and data quality
- Strong problem-solving skills and comfort operating in ambiguous, fast-changing environments
- Demonstrated ability to independently drive solutions from requirements gathering through deployment and iteration
- Proven ability to collaborate cross-functionally across engineering, product, operations, data and business teams
Nice To Haves
- Japanese language proficiency, with the ability to communicate effectively with Japanese-speaking customers and stakeholders and understand technical and business requirements in Japanese.
- Experience working in startup or high-growth environments with rapidly evolving priorities
- Strong product intuition and business empathy, with the ability to influence product direction based on field feedback
Responsibilities
- Partner directly with business stakeholders, engineers and product managers to understand operational workflows, deployment requirements and process bottlenecks
- Translate ambiguous business needs into practical, scalable technical solutions
- Identify high-impact operational pain points and rapidly deliver solutions that create measurable value
- Scope, design, build and deploy AI-powered internal tools, workflow automations and system integrations across test and production environments
- Lead business implementations and deployments as a Forward-Deployed Engineer / Technical Product Manager (FDE/TPM)
- Build and maintain integrations across APIs, systems and data platforms
- Design and implement data pipelines and ETL/ELT workflows to ingest, clean, transform, validate and prepare data for AI and data-intensive applications
- Work with large, complex and heterogeneous datasets across multiple enterprise systems and data sources
- Develop data-processing workflows that combine structured and unstructured data, including databases, spreadsheets, documents, APIs and other enterprise data sources
- Establish data quality checks, validation processes and monitoring to ensure data is reliable and usable by downstream applications
- Troubleshoot data pipelines and investigate issues related to data quality, schema changes, ingestion failures, transformation errors and data availability
- Work with engineering teams to design data architectures and pipelines that support scalable AI applications, analytics and automation workflows
- Troubleshoot production issues, debug live environments and drive issues through resolution
- Guide user adoption, training and iterative improvement as workflows and AI capabilities evolve
- Partner closely with product and engineering teams to improve platform capabilities based on real-world operational feedback
- Operate effectively in dynamic environments with evolving business and deployment requirements
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
