Top Tech Jobs & Startup Jobs

Develop and maintain Python data pipelines and CI/CD deployments to build business data objects. Interpret design requirements, implement source-to-target mappings, write unit/integration tests, and resolve complex application issues while promoting software quality and team improvement.

Lead data architecture efforts to design scalable database and data solutions, define data management strategy, enforce data quality and governance, document domain data models, and provide technical leadership across teams to support applications, analytics, and BI use cases.

Lead end-to-end system integration for autonomous solutions, aligning domain product teams, system engineering, safety, data, and deployment. Own system-level backlog, define acceptance criteria, manage dependencies, risks, and tradeoffs, drive roadmap alignment, integration readiness, milestone decisions, and deliver cohesive mission outcomes across multiple scrum teams and product domains.

Lead end-to-end machine deployment lifecycle: define strategy and roadmap, manage integrated master schedule, prioritize backlog, coordinate procurement, assembly, validation, testing, logistics, shipment, and site delivery. Make deployment decisions, define acceptance criteria, and communicate readiness, risks, and milestones while partnering with Engineering, Supply Chain, Manufacturing, Test & Validation, and customers.

Modernize a legacy FORTRAN business simulation by converting it to C++, validate with stakeholders, and support data science initiatives including ML, NLP, inventory optimization, simulation, and Power BI reporting using large datasets.

Lead strategy, roadmap, and delivery for data collection, labeling, quality, and scalable pipeline products that enable AI/ML, analytics, and autonomous systems. Own product backlog, define acceptance criteria, set data quality and governance standards, prioritize data acquisition and annotation, and coordinate cross-functional engineering and data teams to deliver production datasets and platform capabilities.

Lead customer adoption strategy for autonomous solutions, owning backlog, deployment wave planning, customer selection, go-to-market and deployment readiness. Coordinate cross-functional teams to define acceptance criteria, onboarding, training, milestones, and success metrics to ensure timely delivery and business value realization for autonomous implementations.

Design, develop, and maintain API platform solutions on Apigee and GCP. Implement secure, contract-first REST/SOAP APIs, automate testing and infrastructure (Terraform), support migrations, and operate platform reliability, security, and governance.

The Engineering Manager leads the IAM Platform team, focusing on operational leadership, SRE implementation, automation, AI integration, and team development to ensure stability and innovation in identity management.

Lead multiple engineering teams to deliver simulation integration, digital twin and geospatial/safety platform services. Define reusable platform APIs, collaborate with product and security, scale engineering execution, and improve organizational efficiency while ensuring reliability, performance, and security.