What is the project, and why should you care? At Symphony Solutions, you will work closely with a portfolio of Symphony Solutions Centers of Excellence in Airlines and Aviation, as well as other domains, collaborating with and receiving support from various teams across the organization, including the Tech Office, Software Engineering, DevOps and Cloud Engineering, Business Analysis, Tech Leads, and Solutions Architecture teams.
As a Technical Lead, you will take ownership of the technical development practices across the product team(s). You will manage the technical backlog and act as the key interface between Product Owner(s), Architecture, and Engineering teams.
The project is a cloud-native aviation analytics and automation platform that ingests flight and invoice data, calculates true air traffic control and airport charges using advanced algorithms, and provides airlines with automated validation, discrepancy detection, and financial optimization tools. You will be an excellent fit for this position if you have: Cloud & Platform Engineering (GCP Focus)
— Comfortable with both serverless and containerized solution architectures.
— Understanding of IAM, RBAC, encryption, and general cloud security practices.
Full-Stack Engineering (React + Node.js) * Strong Node.js backend development. * Solid React experience (hooks, modern state management). * Strong TypeScript proficiency across the stack. * Ability to design modular, clean, and scalable full-stack solutions.
Data & Analytics * Proficiency in SQL; strong hands-on experience with BigQuery. * Experience with data ingestion, processing, and transformation for large datasets. * Experience using Python for data-related tasks, automation, or integration workflows. * Familiarity with Jupyter Notebook for exploratory analysis, prototyping, or validation work.
Kubernetes & DevOps Engineering * Practical experience with Kubernetes (preferably GKE). * CI/CD: GitHub Actions, GitLab CI, Cloud Build. * Terraform for IaC. * Familiarity with Helm charts and understanding of Kubernetes operators. * Awareness of secure container, deployment, and DevOps practices.
Architecture, Testing & Code Quality * Strong background in TDD and automated testing. * Good understanding of DDD and scalable architectures. * Familiarity with REST API design principles.
Preferred / Highly Valuable Experience
Geospatial / GIS * Experience working with geospatial data. * Familiarity with PostGIS and spatial queries. * Aviation datasets or standards are a plus.
GenAI, OCR & Private LLM Workloads * Experience with OCR tools (Document AI, Tesseract, ABBYY, etc.). * Experience integrating OCR pipelines with GenAI models. * Experience running private LLMs (self-hosted or controlled environments) for: * Text extraction * Summarization * Intelligent automation * Human-in-the-loop quality workflows * Familiarity with vector databases and RAG pipelines.
Experimental AI Approaches (Nice to Have) * Interest or experience in Spec-Driven AI Development (e.g., generating components/code/tests/specs from formally defined requirements, beyond simple code generation). * Openness to adopt, evaluate, and promote AI-assisted development and QA tools within the team.
Big Data / High-Throughput Systems * Exposure to high-load or large-scale distributed systems. * Useful: Kafka, Apache AirFlow, Dataflow, Flink.
Hybrid and Multi-Cloud Knowledge * Experience building hybrid cloud solutions where sensitive data stays on premises. * Awareness and experience with AWS and/or Azure services is a very strong advantage. * Ability to recognize common multi-cloud patterns and build advanced DRP solutions.
Security & Compliance * Experience in working in Secure SDLC, dependency monitoring. * Experience in regulated industries is beneficial.
Here are some of the things you’ll be working on: Maintainability * Guide teams on design patterns and engineering best practices. * Ensure code quality and maintainable implementation standards. * Manage library/dependency lifecycle. * Oversee code quality tools (SonarQube, linters). * Promote the adoption of AI tools for software development and QA.
Testing * Ensure alignment with QA strategies and testing standards. * Review testing coverage and quality thresholds. * Collaborate with QA, BA, and Product Owners on epic-level functionality. * Mentor developers and assist in structuring technical tasks.
Deployment * Define and improve CI/CD pipelines with the help of DevOps. * Establish branching and deployment strategies.
Security * Identify vulnerabilities and drive remediation. * Manage technical debt related to security.
Observability * Collaborate on monitoring/alerting setups (e.g., Dynatrace). * Review logs, telemetry, and operational signals.
Performance & Scalability * Support performance and load testing. * Identify bottlenecks and provide optimization guidance
