Quick overview
Job description
At Resilinc, we’re not just solving supply chain problems — we’re pioneering the intelligent,
autonomous systems that will define its future. Our cutting-edge Agentic AI enables global
enterprises to predict disruptions, assess impact instantly, and take real-time action —
before operations are even touched. Recognized as a Leader in the 2026 Gartner® Magic
Quadrant™ for Supply Chain Risk Management, we are trusted by marquee clients
across life sciences, aerospace, high tech, and automotive to protect what matters most —
from factory floors to patient care.
But the real power behind Resilinc? Our people. We’re a fully remote, mission-led team
making sure life-saving products and critical goods get where they’re needed, fast. We offer
the chance to do meaningful work in a collaborative, empowering culture—where you can
be an agent of change. Join us to tackle critical global challenges through high-impact work
that matters.
Resilinc | Innovation with Purpose. Intelligence with Impact.
About The Role
B2B SaaS platform.
This is an ownership-driven engineering role where you will be responsible for the end-toend
delivery of features, platform modules, and engineering initiatives—from understanding product requirements and technical design to implementation,deployment, and production support. You'll collaborate closely with Tech Leads, Architects, Product Managers, QA, and other engineering teams to deliver reliable, scalable, and maintainable software.
What You'll Do
- Own the end-to-end delivery of backend features, platform modules, and engineering initiatives from design through production.
- Design, develop, and maintain scalable backend services, distributed data pipelines, and ingestion frameworks that process data from multiple enterprise sources.
- Build and maintain production-grade Python web services and REST APIs using modern frameworks such as FastAPI, Flask, and Quart to support scalable backend applications and data ingestion services.
- Design and optimize distributed data processing pipelines using PySpark and SQL for large-scale data processing.
- Architect, build, and enhance scalable data ingestion frameworks that process structured and semi-structured data from enterprise APIs, databases, cloud storage, and multiple file formats.
- Drive improvements in platform scalability, reliability, observability, performance, and maintainability.
- Collaborate with Product Managers and Architects to translate business requirements into scalable technical solutions.
- Break down large engineering initiatives into deliverable work items and drive execution across the team.
- Perform code reviews, mentor junior engineers, and promote engineering best practices across the team.
- Troubleshoot complex production issues and lead root cause analysis to improve platform stability.
- Champion engineering excellence by adopting modern tools, AI-assisted development practices, and continuous improvement initiatives.
What You Will Bring
-
4–6 years of experience in backend engineering or data engineering, preferably in a scalable B2B SaaS product environment.
-
Strong programming skills in Python, with experience building scalable backend applications.
-
Hands-on experience building distributed data processing pipelines using PySpark.
-
Strong SQL skills, including complex query development, query optimization, and relational database design.
-
Strong experience developing REST APIs and Python web services using FastAPI, Flask, or Quart.
-
Experience building scalable ETL/ELT pipelines and enterprise data ingestion frameworks.
-
Experience working with cloud platforms such as Microsoft Azure (preferred) or AWS.
-
Hands-on experience with Git, CI/CD, and modern software engineering practices.
-
Strong debugging, performance tuning, and problem-solving skills.
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Proven experience independently delivering features, modules, or projects from requirements through production.
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Ability to estimate work, identify technical risks, and drive timely delivery.
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Strong ownership mindset with excellent collaboration and communication skills.
-
Comfortable leveraging AI-assisted development tools such as GitHub Copilot, Cursor, ChatGPT, and Claude to improve engineering productivity, code quality, debugging, and problem-solving.
What Will Make You Stand Out
-
Experience working in a B2B SaaS, supply chain, compliance, or other data-intensive product company, preferably in a high-growth environment.
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Exposure to supply chain operations, compliance, or risk management domains.
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Experience working with modern cloud data platforms such as Databricks (preferred), Snowflake, and Lakehouse technologies, including Delta Lake.
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Experience designing scalable backend architectures and distributed systems.
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Exposure to one or more of the following technologies: Java, Kafka, Redis, Apache Airflow, or Kubernetes.
-
Experience mentoring engineers and contributing to technical design discussions.
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