VP, Development- REMOTE

Job Summary We're looking for a highly technical and execution-driven Vice President of Development to scale our clients fully remote engineering organization. This role is ideal for an accomplished leader who thrives in fast-paced environments, loves solving complex problems, and brings both deep technical expertise and proven management across multiple teams and domains. As the senior engineering leader supporting the CTO, you'll serve as the operational engine of the technology organization—driving delivery, ensuring cross-team alignment, and instilling discipline in execution.

You'll help shape engineering strategy and architecture while ensuring secure, scalable, and high-quality solutions across customer applications, backend systems, and large-scale data infrastructure. Primary Responsibilities Engineering Leadership & Management Lead, mentor, and scale distributed teams across software, platform, qa, devops, and data. Drive execution of strategic initiatives with a focus on alignment, timely delivery, and quality outcomes.

Establish clear and consistent processes for planning, execution, and accountability across teams. Build a strong engineering culture that values collaboration, ownership, and technical excellence, while elevating problem‑solving so engineers think strategically about trade‑offs, system design, and long‑term impact—not just task execution. Architecture, Data, & Security Guide the design and evolution of system and data architectures to support enterprise growth initiatives.

Oversee data infrastructure, pipelines, and delivery systems to ensure scalability, reliability, and security. Lead cloud modernization, DevOps, and security initiatives while ensuring compliance with industry standards and regulatory requirements. Provide technical oversight on critical systems and architecture decisions.

Cross‑Functional Collaboration Partner with Product, Data, and business leaders to align priorities and improve planning discipline. Work with cross‑functional partners to design delivery systems and frameworks that are fast and efficient. Ensure projects have clear definitions of readiness and completion, reducing ad‑hoc execution.

Act as a bridge between technical and business stakeholders, driving clarity and alignment. Qualifications Technical Skills Years as a software engineer—strong in full‑stack and backend development. Deep expertise with React, TypeScript, Python, and Proven track record building and scaling APIs (GraphQL and REST).

Strong database and data modeling skills—PostgreSQL preferred. Experience with monorepos, modular architectures, and microservices. Skilled in building and integrating ETL / data pipelines.

Experience building data processing and integration logic using Python, SQL, with attention to performance, scalability, and maintainability. Hands‑on with modern data platforms (Snowflake, Databricks, Apache Airflow, dbt, AWS Glue). Strong understanding of AWS, CI / CD workflows, and containerization (Docker, Kubernetes).

Comfortable with TDD and automated testing frameworks. Solid grasp of software architecture principles (SOLID, DDD, DRY). Experience with both greenfield and legacy systems.

Exposure to admin tools and internal platforms development. Knowledge of data observability, schema governance, or data lineage tooling. Exposure to ML pipelines, BI tools, or product instrumentation.

Familiarity with mobile frameworks (React Native, Capacitor). Leadership & Business Skills Years in engineering leadership; years leading multi‑team orgs in SaaS & Data. Proven ability to build, lead, and mentor distributed teams in high‑growth environments.

Strong communicator able to bridge technical and business priorities. Experienced in shaping engineering culture and driving organizational excellence. Skilled at bringing structure, discipline, and focus to fast‑paced, complex environment.

Bonus Skills Experience in healthcare, life sciences, or regulated data environments. Background in governance, compliance, data lineage, schema evolution, and data quality. Exposure to ML pipelines, recommendation systems, or advanced analytics.

Familiarity with AI / ML model deployment, vector databases, or RAG architectures. Hands‑on knowledge of AI‑powered product features—including LLM integrations, intelligent automation, and personalized, data‑driven solutions. Track record of working closely with CTOs, CEOs, and technical founders in scaling, high‑growth companies. #J-18808-Ljbffr