Forward-Deployed Engineer - Global Sourcing & Supply Management (GSSM) Solutions
Apple Bengaluru, Karnataka, India
Computers and Electronics Manufacturing · 10,001+ employees
About the role
You will work at the intersection of engineering and product to identify operational pain points and deploy AI-powered solutions. This involves building and operationalizing data pipelines, APIs, and automated workflows to solve complex business problems.
What they look for
Requirements
Candidates must have a Bachelor's or Master's degree in a technical field and 4-7 years of experience in software or data engineering. Strong proficiency in Python, SQL, and data pipeline design is required, along with the ability to operate in ambiguous environments.
Full description
Imagine what you could do here. At Apple, great ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish.
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.
Description
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.
Minimum Qualifications
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
Preferred Qualifications
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 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
