Lead Full Stack Software Engineer at Blend360

Columbia, Maryland, United States -

Full Time

Start Date

Immediate

Expiry Date

06 Jan, 26

Salary

0.0

Posted On

08 Oct, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

React, Google Cloud Platform, BigQuery, Node.js, Python, API Design, Microservices Architecture, Data Pipelines, Analytics, AI/ML, Agile, Coding Best Practices, Security Best Practices, Testing Best Practices, DevOps, Mentoring

Industry

Professional Services

Description

Company Description Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. For more information, visit www.blend360.com. Job Description As a Lead Full Software Engineer, you'll play a critical role in designing, building, and scaling modern data and application architectures for our clients. You’ll lead technical teams and partner with stakeholders across disciplines to deliver high-impact solutions—leveraging your deep expertise in React, Google Cloud Platform (GCP), and BigQuery to architect end-to-end platforms that are as elegant as they are effective. You’re not just a coder—you’re a builder, a leader, and a translator between business needs and technical execution. You’re excited by the opportunity to guide both the vision and the implementation of transformative technology solutions. What You’ll Do Architect and develop full-stack solutions that deliver measurable business value, with a strong focus on cloud-native applications using GCP. Design and implement scalable front-end experiences using React, integrating seamlessly with backend services and data layers. Build and optimize data pipelines leveraging BigQuery and other GCP-native tools for analytics, AI/ML, and real-time data needs. Lead and mentor high-performing technical teams across architecture, development, and delivery. Act as the technical lead in cross-functional client engagements, driving solutioning from concept through production deployment. Establish and enforce best practices in coding, security, testing, and DevOps across projects. Collaborate closely with data scientists, analysts, and business stakeholders to align technology solutions with business goals. Qualifications 5-8 years of experience in software engineering, with 1-3 years in an architecture or technical leadership role. Proven expertise in React (hooks, state management, performance tuning) and building responsive, accessible UIs. Deep hands-on experience with Google Cloud Platform, especially BigQuery and other OLAP and OLTP data sets. Strong proficiency in back-end development (Node.js, Python, or similar), API design, and microservices architecture. Experience designing systems that handle large-scale data ingestion, transformation, and analytics. A strategic mindset and the ability to translate business challenges into scalable tech solutions. Comfortable working in agile environments, with a bias for action and a focus on delivering value fast. Excellent communication skills and a track record of leading technical teams and mentoring engineers. Nice to Have Experience with Looker, dbt, or other modern data stack tools. Familiarity with AI/ML workflows on GCP. Exposure to CI/CD pipelines, Terraform, or Infrastructure as Code (IaC).

Responsibilities

Architect and develop full-stack solutions that deliver measurable business value, focusing on cloud-native applications using GCP. Lead and mentor high-performing technical teams while collaborating with stakeholders to drive solutions from concept through production deployment.