Software Engineer

Backend EngineerTraackr is a global SaaS technology company providing a data-driven influencer marketing platform that marketers use to optimize investments, streamline campaigns, and scale programs. Our customers range from some of the world's largest companies in the beauty and personal care space to digitally native indie brands, which have all made influencer management and engagement a critical practice of their marketing and advertising programs. We are a remote-first company, and for the folks that like to meet in person, we have offices in San Francisco, New York, Boston, Paris, and London. We operate on a culture of mutual respect, with core value pillars including:TrustDiversityValueOwnershipMutual successThis position is 100% remote, with the understanding that occasional in-person attendance may be required for trainings, meetings, and team gatherings, as determined by your manager.Responsibilities:Own backend features end-to-end: discovery, design, implementation, rollout, and ongoing reliability and operations, with support from more experienced teammates as needed.Help design and evolve distributed systems (services, pipelines, and data stores) with an eye toward performance, scalability, and resiliency.Build and maintain APIs and data access patterns that support analytics and search use cases.Develop, maintain, and optimize scalable data pipelines that power product features, analytics, and machine learning workloads.Ensure data reliability, quality, and performance across our systems, and monitor and troubleshoot pipelines to ensure consistent, timely delivery.Build strong engineering habits: thoughtful code reviews, solid testing, incident readiness, and operational excellence.Apply an experimentation-first approach: define hypotheses and success metrics/guardrails, run controlled rollouts and A/B tests when appropriate, and write clear readouts for stakeholders.Use AI coding tools like Claude Code productively and responsibly as part of your development workflow - for implementation, debugging, refactoring, and design reviews - while maintaining high standards for correctness, security, and privacy.Bring evaluation discipline to AI-assisted work: treat prompts and configs like versioned artifacts, design regression tests, measure quality changes, and monitor for drift the same way you would for performance or correctness.Grow continuously: actively seek feedback, learn new tools, languages, and domains quickly, and apply what you learn to your work.Collaborate with Product Managers and fellow Engineers to ship intelligent, data-driven products.Share knowledge with teammates through clear documentation, pairing, and participation in code reviews.Document systems, pipelines, and architecture, and help evolve our engineering best practices.Stay current with emerging tools, frameworks, and trends across software, data, and AI engineering.Requirements:2-4 years of professional software engineering experience building backend systems, and a desire to grow into larger distributed systems challenges.A growth mindset: curiosity, a habit of learning new tools and domains quickly, and openness to feedback.Strong general-purpose programming skills and software engineering fundamentals.Solid debugging skills and the ability to troubleshoot and performance-tune production services.Strong SQL and data modeling skills.Experience with version control (Git) and CI/CD workflows.Comfort using AI coding assistants like Claude Code as part of your workflow, and the discipline to validate outputs (tests, metrics, evaluation) rather than trusting them blindly.Strong problem-solving and communication skills, and the ability to collaborate across functions.Nice to have:Experience building and maintaining data pipelines (ETL/ELT).Exposure to event-driven architectures, cloud deployment on AWS, and containers (Docker/Kubernetes).Hands-on experience building or deploying AI/ML-powered features or data-driven products.Familiarity with machine learning workflows, including data preparation, training, and deployment.Familiarity with ML libraries/frameworks (e.g., scikit-learn, TensorFlow, PyTorch, or similar).Exposure to LLMs, NLP, or generative AI use cases.Experience with Databricks, Apache Spark, or similar distributed data platforms (including cost monitoring and optimization).Experience deploying ML models using MLOps tools (e.g., MLflow, Airflow, Kubeflow).Experience with workflow/orchestration tools (Airflow, Argo, Dagster), Terraform/Ansible, and Grafana dashboards.Search/retrieval systems (Elasticsearch/Lucene) and GraphQL.Understanding of real-time or streaming data pipelines.$90,000 - $120,000 a yearBenefits:Competitive SalaryRemote Work Options with Hybrid Flexibility and Home Office Set-Up StipendCoworking Office Subscription for Collaborative SpacesHealth, Dental, and Life Insurance Coverage*Open Vacation Policy and Flexible Holiday Schedule to Suit Your NeedsPaid Parental Leave to Support Quality Time with Your Loved OnesCareer Development, including Internal and External Training OpportunitiesTraackr employs individuals in multiple US states and countries. We use market benchmark data and geographic zones to determine our salary ranges. Your zone's specific pay range is dependent on your home location. We encourage you to discuss your zone-specific pay range with your Traackr recruiter for more details.Benefit programs vary by country/state of residency, are subject to eligibility requirements, and may be modified from time to time. Ask for more details about the benefits in your specific region.Traackr is an Equal Employment Opportunity employer. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other legally protected characteristics. All your information will be kept confidential in accordance with EEO guidelines.