Role Overview:

We are seeking a Senior Software Engineer to design and build scalable cloud, Big Data, and machine-learning infrastructure that powers AI-driven Workforce Management capabilities. This role offers the opportunity to solve complex distributed-systems problems, lead projects from design through production, and build reusable platforms that accelerate AI/ML development across multiple teams.

The ideal candidate combines strong software-engineering fundamentals with experience in AWS, distributed data processing, and production platform development. They will influence technical direction, mentor other engineers, and help improve the scalability, reliability, observability, and cost efficiency of our data and ML systems.

The primary responsibilities for this role include, but are not limited to:

• Translate complex business and AI/ML requirements into scalable system designs, technical plans, and production-ready solutions.

• Lead the end-to-end delivery of cloud, Big Data, and ML infrastructure projects from requirements and architecture through testing, deployment, and operational support.

• Design and develop distributed data pipelines and workflow-orchestration services using technologies such as Spark, EMR, S3, Metaflow, AWS Batch, Step Functions, and Fargate.

• Build reusable platform capabilities that enable data scientists and product teams to develop, deploy, and operate AI/ML workflows efficiently.

• Exercise independent judgment when selecting architectures, frameworks, testing strategies, and evaluation criteria for complex technical problems.

• Improve platform reliability, scalability, observability, security, and cost efficiency through performance analysis and architectural enhancements.

• Develop automated, integration, scale, and load tests to validate systems under production-level workloads.

• Collaborate with data scientists, software engineers, product managers, and platform teams to align technical execution with business priorities.

• Define development practices, review technical designs and code, and communicate new methods and procedures to the broader project team.

• Provide technical guidance, coaching, and constructive feedback to junior engineers while learning and collaborating with senior technical leaders.

• Own major technical initiatives, including planning work, coordinating dependencies, delegating tasks when appropriate, and reviewing deliverables.

• Participate in architectural discussions and influence the long-term technical direction of the team’s data and ML platforms.

• Five or more years of relevant professional software-engineering experience, or equivalent experience supported by an advanced degree.

• Advanced programming experience in Python, Java, Scala, or a comparable language.

• Experience designing, developing, and operating production-grade services or distributed data-processing systems.

• Strong experience with AWS services and cloud-native architecture.

• Experience with Big Data technologies such as Apache Spark, EMR, or similar distributed-processing frameworks.

• Demonstrated ability to independently solve complex and ambiguous technical problems.

• Experience owning a project or major technical component from initial design through production delivery.

• Strong understanding of software design, APIs, automated testing, CI/CD, and operational support practices.

• Experience with performance, scalability, reliability, and load-testing methodologies.

• Ability to explain complex technical concepts and influence engineers and internal stakeholders.

• Demonstrated experience mentoring, coaching, reviewing, or providing technical guidance to other engineers.

• Bachelor’s degree in computer science, engineering, or a related technical discipline, or equivalent practical experience.

• Experience with ML platforms, MLOps, model deployment, or AI/ML workflow orchestration.

• Experience with Metaflow, Airflow, Kubeflow, or comparable workflow-management frameworks.

• Experience with AWS Batch, ECS/Fargate, Step Functions, Lambda, DynamoDB, SQS, and Aurora.

• Experience designing secure multi-account or multi-tenant AWS architectures.

• Familiarity with infrastructure-as-code tools such as Terraform, AWS CDK, or CloudFormation.

• Experience implementing observability using CloudWatch, OpenTelemetry, New Relic, or similar platforms.

• Experience optimizing cloud infrastructure for performance and cost.

• Familiarity with workforce management, forecasting, anomaly detection, or Agentic AI applications.

Compensation:

This role has a market-competitive salary with an anticipated base compensation range listed below. Actual salaries will vary depending on a candidate’s experience, qualifications, skills, and location. This role might also be eligible for a commission or performance-based bonus opportunities.