Software Engineer
Boston, NH - USA
Department:
Job Summary
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.
Required Experience:
IC
About Company
Use Traackr's influencer marketing software to find influencers, manage influencer campaigns, and access insightful reporting. Built to handle the most complex programs, yet nimble enough for small teams that need to do it all.