The Role

Fusion is a global electronics distributor building a modern data platform on top of a 20 year old legacy system. Palantir Foundry is a core part of that stack. We use it to deliver unified views of our customers, products, and operations, and we are leaning hard into AIP and agent driven workflows to compress delivery cycles. We are looking for a senior engineer who can work hands on in Foundry: building pipelines, ontology models, agents, and applications alongside our external Palantir consultants today, and progressively taking ownership as the platform matures.

This is an execution focused role with real autonomy. You will design and build solutions, work directly with business stakeholders, and have a voice in how the platform evolves.

What You’ll Do

• Build and maintain data pipelines: Design, build, and optimize batch and streaming pipelines in Foundry (Pipeline Builder with AI assist, Code Repositories, Code Workbook) that ingest data from internal and external source systems.
• Develop ontology models: Create and maintain ontology objects, relationships, link types, functions, and actions that represent business domains and power downstream applications, agents, and AIP workflows.
• Build AI native experiences with AIP: Use AIP Logic to compose AI driven functions, AIP Agent Studio to stand up domain agents, and AIP Threads or AIP Assist to embed conversational interfaces into Workshop apps. Use AIP Evals to validate prompt and agent behavior before promotion to production.
• Leverage AIP Analyst and FDE AI for delivery acceleration: Use AIP Analyst for ad hoc analytical work directly against the ontology, and lean on FDE AI and Solution Designer to scaffold ontology objects, pipelines, and starter applications. Refine the AI generated output, harden it for production, and bring it under proper change control.
• Deliver Foundry applications: Build and iterate on Workshop, Quiver, and Contour applications that give sales, operations, and leadership actionable views of the business, including embedded agentic actions and write back through Ontology Actions.
• Work alongside external consultants: Collaborate closely with our Palantir implementation partners to understand existing designs, validate data flows, and progressively take on more of the day to day Foundry work.
• Connect Foundry to the broader data platform: As the data modernization team builds out medallion layer domain stores and DBT based pipelines on Azure, help align Foundry’s ontology and ingestion paths so the platform can transition from legacy sources to the new architecture cleanly.
• Integrate with external systems: Build and maintain OSDK based integrations and APIs that connect Foundry to internal services and third party platforms.
• Engage stakeholders directly: Gather requirements from business teams, demo solutions, train end users, and incorporate feedback into iterations.
• Ensure data quality and observability: Implement validation, lineage tracking, health checks, and monitoring within Foundry pipelines. Build automated data quality checks, including AIP assisted ones, to keep data accurate and reliable.
• Apply AI tooling to your own workflow: Use AIP and AI assisted development practices to accelerate pipeline work, code review, and documentation.

What You Bring

Data Engineering Foundations

These are the bedrock skills we expect every senior data engineer on this team to have, regardless of platform. Foundry is the surface; these are the muscles underneath.

• 7+ years building production data pipelines in modern stacks.
• Strong SQL, including window functions, CTEs, set operations, and query optimization on large datasets. You can read an execution plan and explain the cost.
• Solid grasp of dimensional modeling (Kimball, star schema), Data Vault, or equivalent. You can defend a modeling choice with reasoning, not dogma.
• Experience designing for slowly changing dimensions, idempotent loads, late arriving data, backfills, and incremental processing.
• Proficiency in Python, including PySpark and pandas for transformation work.
• Working knowledge of the Spark execution model: partitioning, shuffles, skew, broadcast joins, and tuning.
• Experience with ETL and ELT patterns, CDC pipelines, and workflow orchestration.
• Familiarity with modern transformation frameworks such as DBT, including tests, documentation, snapshots, and incremental materializations.
• Understanding of columnar formats (Parquet, Delta, Iceberg), table formats, and partitioning strategies.
• Practical experience implementing data quality frameworks, data contracts, and SLAs between producers and consumers.
• Comfort with Git workflows, code review, branching strategies, and CI/CD for data platforms.

Palantir Foundry and AIP

• 2+ years hands on Palantir Foundry experience with delivered work you can describe in detail.
• Strong knowledge of core Foundry capabilities: Ontology Manager, Ontology Functions and Actions, Pipeline Builder, Code Repositories, Code Workbook, Workshop, Builds, and platform security (branching, resource allocation, rollbacks).
• Experience with Foundry analytical and integration tools: Quiver, Contour, OSDK, and Marketplace products.
• Hands on experience with AIP for augmenting data workflows: AIP Logic, AIP Assist and Threads, and AIP assisted Pipeline Builder.
• Familiarity with newer AIP surfaces is a strong plus: AIP Agent Studio, AIP Analyst, FDE AI and Solution Designer, AIP Evals, and Automate.
• Understanding of how to evaluate, guardrail, and version AI driven functions and agents in a production context.

Cloud, Architecture, and Stakeholder Skills

• Proficiency with Azure data services, or equivalent depth in AWS or GCP with willingness to work in Azure.
• Solid understanding of data modeling across relational, analytical, and document paradigms.
• Ability to translate business requirements into technical designs and explain trade offs to non technical stakeholders.
• Self directed work style. You identify what needs doing and get it done without waiting for direction.

Nice to Have

• Production experience with DBT on Azure (Synapse, Fabric, or Databricks).
• Experience with medallion architecture (Bronze, Silver, Gold) or lakehouse patterns on Databricks, Snowflake, or equivalent.
• Experience evaluating LLM powered features: prompt design, eval harnesses, hallucination guardrails, and cost or latency tuning.
• Experience building or operating real time pricing, recommendation, or scoring engines.
• Familiarity with electronics distribution, supply chain, or ERP data, particularly Dynamics GP and Great Plains.
• Background in domain driven design or microservices architecture.
• TypeScript or C# for OSDK consumers and downstream services.
• Exposure to CRM, payment, or logistics API integrations.

Why Fusion

• Greenfield meets legacy: You’ll help build a modern data platform while keeping a 20 year business running. Real engineering problems, not toy projects.
• Real impact, small team: A lean team where your work is visible and your judgment matters. No layers of approval.
• AI first engineering culture: We use AIP and AI tooling aggressively. One engineer with the right tools does the work of three.
• Global scale: Fusion operates across the US, Singapore, and Hong Kong. The platform serves users worldwide.

Job Description

Fusion Worldwide is looking for a hands-on developer who can both build applications and stand up the infrastructure they run on. This role sits at the intersection of software engineering and day-to-day operations — you will own solutions end-to-end, from database design and deployment pipelines through to the application layer and operational dashboards.

You'll significantly shorten the time between an operational need and a working solution. We prioritize shipping working tools quickly, then hardening them as they prove their value.

What We Can Do For You

• Offer support through a collaborative, open environment alongside seasoned professionals with decades of industry expertise.
• Enable career growth through direct and focused mentorship.

What You Can Do For Us

Key Responsibilities

• Design, develop, and deploy automation and AI-assisted solutions for warehouse and test lab operations.
• Set up and maintain the deployment infrastructure these tools run on — databases, application hosting, CI/CD, backups, and monitoring.
• Design and operate data pipelines that ingest equipment data from warehouse systems and Prosemi test lab machines into centralized, queryable stores for real-time monitoring and automation.
• Build and maintain barcode label recognition and authentication systems using OCR and computer vision techniques.
• Develop inventory auto-count and verification workflows that reconcile physical stock against database records in real time.
• Manage the on-premise and/or cloud environments where these systems run, including networking between warehouse equipment and centralized services.
• Implement basic security and access controls — authentication, secrets management, and network segmentation between equipment and corporate systems.
• Work closely with the engineering team to ensure solutions follow company standards and remain maintainable at scale.
• Iterate rapidly on released solutions — applying updates, feature additions, and adjustments with minimal turnaround time.
• Own runbooks and documentation for the tools you build so operations teams can self-serve.

What you will work on

• Barcode AI recognition — OCR and vision-based label reading and authentication to reduce manual verification errors.
• Inventory auto-count — Automated physical inventory counting with real-time database cross-verification.
• Machine data integration — Connecting test lab and warehouse equipment to structured data pipelines.
• Operational dashboards — Visibility tools that surface key metrics to operations and quality teams.

Who We’re Looking For

• 5+ years of software development experience, including at least 2 years operating production systems you built yourself.
• Minimum of a Bachelor’s Degree in computer science or a related discipline is required for this role.
• Strong backend development skills in Python (or similar), with solid fundamentals in API design, async processing, and database modeling. Comfortable with both SQL and NoSQL — and knows when to use which.
• Hands-on experience deploying and operating production systems: containers (Docker), at least one cloud platform (AWS/Azure/GCP) oron-prem Linux administration, CI/CD pipelines, and basic observability (logs, metrics, alerts).
• Experience designing and running data pipelines that ingest from external sources (APIs, hardware, files) into a queryable store.
• Comfortable with networking fundamentals — TCP/IP, firewalls, VPNs — and connecting industrial or warehouse equipment to backend services.
• Familiarity with AI/ML APIs or frameworks for vision tasks (OCR, object detection, classification). You don't need to train models from scratch, but you should know how to integrate and fine-tune existing ones.
• Comfortable working in an operational environment — able to gather requirements directly from non-technical stakeholders and translate them into working systems.
• Strong ownership: you can take a project from a vague operational need through to a deployed, monitored, documented solution.

      Good to have

• Exposure to industrial equipment data protocols (Modbus, MQTT, OPC-UA, serial, vendor REST APIs).
• Experience with computer vision or barcode/OCR technologies (YOLO, Tesseract, ZXing/pyzbar, cloud vision APIs).
• Message queues or streaming tools (RabbitMQ, Kafka, Redis Streams).
• Background in warehouse management systems (WMS) or laboratory information management systems (LIMS).
• Experience in electronics distribution, semiconductor, or supply chain environments.

Benefits

• Attractive salary package with medical and dental benefits.
• Modern, open-concept working environment.
• Collaborative and motivated team culture.
• Supportive management invested in your success.
• Smart casual dress code.
• Conveniently located within walking distance from Taiseng MRT station.