We're looking for a Senior Software Engineer who can operate independently within an Agile team, take ambiguous requirements from concept to production, and bring architectural judgment to how we structure and process data at scale. This is not a developer from a particular tech stack, but rather a true software engineer who can and will work with any number of languages without restriction.
We are only accepting candidates currently residing in the state of Florida, Georgia or Texas at this time.
Responsibilities
Work within a Scrum/Agile team through the full sprint cycle — backlog refinement, sprint planning, capacity estimation, daily standups, sprint review, and retrospectives.
Participate in requirement refinement sessions with product owners and stakeholders, turning ambiguous asks into well-scoped, estimable stories.
Apply modern software design patterns and enforce separation of concerns across the codebase, ensuring components remain loosely coupled and independently testable.
Design and build proofs of concept (POCs) to validate new approaches before committing to full implementation.
Integrate AI/ML and/or NLP components into production systems.
Design and implement systems that handle structured (CSV, relational), semi-structured (JSON), unstructured, and schema-bound formats like Avro, including the tradeoffs between them for storage, processing and schema evolution.
Contribute to big data architecture and design patterns — batch and/or streaming pipelines, data partitioning, and scalable processing approaches.
Collaborate with UI/UX on interface design decisions, ensuring frontend implementation aligns with usability and design intent.
Mentor junior developers through code review, pairing, and design discussions.
Required Qualifications
Proven experience working in Scrum/Agile teams, including sprint planning, capacity estimation, and iterative delivery.
Strong grasp of modern design patterns (e.g., strategy, factory, repository, observer) and the "separation of concerns" principle — able to explain not just what it is, but why it matters for maintainability and testability.
Experience with UI/UX collaboration and requirement refinement.
Hands-on experience with structured, semi-structured, unstructured, and schema-based data formats (CSV, JSON, Avro).
Big data technology experience (e.g., Spark, Kafka, Hadoop ecosystem or equivalent) and associated design patterns.
Demonstrated experience building and validating POCs.
Experience designing and building microservices architectures — service decomposition, inter-service communication (REST/gRPC/event-driven messaging), API contracts and independent deployability.
Strong understanding of data layer and persistence design patterns — repository pattern, unit of work, CQRS, data access layer abstraction, ORM vs. raw query tradeoffs, caching strategies and both relational (SQL) and NoSQL database design.
Experience with cloud platforms — AWS, Azure or Google Cloud Platform (GCP) — including core compute, storage, and managed data services on at least one major provider.
Experience with Machine Learning, NLP or AI — applied experience integrating AI/ML components into production systems.
Desirable
Proficiency in one or more modern languages beyond your primary stack — Python, Scala, Go, Java, Kotlin, Rust, TypeScript/Node.js or C# — with the versatility to pick up new languages as project needs evolve.
Multi-cloud exposure across AWS, Azure, and GCP, and familiarity with cloud-native patterns (containers, Kubernetes, serverless, managed data/streaming services).