Director, Software Engineering

Suvoda LLC
Conshohocken, United States of America
yesterday

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Conshohocken, United States of America

Tech stack

API
Agile Methodologies
Agile Methodologies
Artificial Intelligence
Amazon Web Services (AWS)
Business Analytics Applications
Software as a Service
Cloud Engineering
Code Generation
Code Review
Information Systems
Continuous Integration
Data Architecture
Data Warehousing
Cursor (Graphical User Interface Elements)
Distributed Systems
Django
Amazon DynamoDB
Python
PostgreSQL
Object-Relational Mapping
Systems Development Life Cycle
Redis
Reliability Engineering
Cloud Services
Software Engineering
Software Organization
Spring Cloud
GitHub Copilot
Amazon Web Services (AWS)
System Availability
Large Language Models
Prompt Engineering
Technical Debt
AWS Lambda
Containerization
Angular
Information Technology
Terraform
Microservices

Job description

The Director, Software Engineering is responsible for the delivery of Enterprise SaaS products supporting the Clinical Trial industry, overseeing multiple on-shore and off-shore development teams and the delivery of multiple products and initiatives. The Director, Software Engineering provides strategic planning and tactical execution management, agile release planning across multiple teams, process and tool design, resource management, and continuous improvement. The role demands a blend of technical and business acumen, strategic and tactical focus, and an ability to balance architectural best practice and innovation pragmatism. In a typical business day, the Director, Engineering may find themselves pair-programming with developers on a priority feature or defect and briefing the C-suite on roadmap direction and key technical decisions. Responsibilities

  • Works with the SVP of Engineering to build a technical vision for the product line.
  • Explores new technologies for future planning and potential implementation and evaluates and identifies appropriate technology to deliver business objectives.
  • Ensures engineering best practices are defined and met across teams and develops and governs technical standards to ensure adherence.
  • Collaborates with architects and principal engineers in the technical design of initiatives and business priorities.
  • Experience leading distributed or cross-functional teams globally, including recruiting, mentoring, and retaining team members in a continuous improvement environment. Provides leadership and professional growth with the goal to build our next generation of engineering leaders.
  • Extensive knowledge of enterprise architecture patterns, microservices, and distributed systems design.
  • Experience with enterprise SaaS architecture and development in a product-driven environment, including multi-tenancy, scalability, and platform reliability at scale.
  • Fluency in data architecture concepts including data models, data warehouses, analytical platforms, and modern data mesh or lakehouse patterns.
  • Familiarity with service portfolio management, API governance, and technical debt prioritization at the enterprise level.
  • Works closely with Product Management and Architecture to discover business requirements and technical approach for product initiatives and features.
  • Supports teams in the discovery and design of product backlog items and identifies and manages cross-organization dependencies.
  • Develop Proof of Concept solutions to demonstrate technical design and can dive into the code and pair program with engineers as necessary.
  • Initiates and drives continuous improvement initiatives, challenges self and teams to continuously grow and achieve new levels of success.
  • Will be held accountable for the design, development, and delivery of Suvoda product and solutions.
  • A "team-player" with the ability to work within a highly collaborative environment.
  • A creative and critical thinker that is able to confidently express ideas in an articulate, concise manner.

Requirements

  • Bachelor's degree in Computer Science, Information Systems, Mathematics, Engineering or equivalent relevant work experience and/or training.
  • At least 10 years of progressive experience in the software industry, including at least 5 years in a leadership position.
  • Proven experience delivering cloud-native applications on AWS, including IaC tooling (Terraform), container orchestration (EKS), and cloud cost optimization.
  • Good working knowledge of Python, Django ORM, Django REST Framework, and Angular for building and maintaining scalable Back End and Front End services; hands-on familiarity with event-driven cloud service architectures leveraging AWS Lambda, DynamoDB, ElastiCache (Redis), and Postgres RDS.
  • Strong experience managing people and teams; setting goals, providing clear technical direction, and holding teams accountable for delivering business value.
  • Strong experience with software development best practices and tooling, agile testing, developer operations, continuous integration and delivery, and site reliability engineering.
  • Relevant technical knowledge of enterprise architecture, cloud services, cloud development, containerization, business domain modelling, data warehouses and analytical platforms.
  • Proven experience in Agile Software Development methodology.

Nice to Have

  • Hands-on experience adopting and governing AI coding assistants (eg, Claude, GitHub Copilot, Cursor) across engineering teams, including establishing standards for responsible use, prompt engineering best practices, and measuring productivity impact.
  • Familiarity with Anthropic's Claude API or Claude Code for agentic developer workflows, including task automation, code generation pipelines, and AI-assisted code review.
  • Experience integrating LLM-powered tooling into the SDLC - such as AI-assisted test generation, documentation automation, or intelligent PR summarization.
  • Demonstrated ability to lead organizational change around AI adoption - including upskilling teams, establishing guardrails, and balancing developer autonomy with governance.
  • Familiarity with prompt engineering principles and the ability to coach engineers on effective human-AI collaboration patterns.

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