Sr Software Engineer

Company Cox Automotive - USA
Job Family Group Engineering / Product Development
Job Profile Sr Software Engineer
Management Level Individual Contributor
Flexible Work Option Hybrid - Ability to work remotely part of the week
Travel % No
Work Shift Day

Compensation includes a base salary in the range of $ - $. The base salary may vary within the anticipated base pay range based on factors such as the ultimate location of the position and the selected candidate’s knowledge, skills, and abilities. Position may be eligible for additional compensation that may include an incentive program.

The Senior Software Engineer is a hands‑on leader responsible for driving the full-stack design, development, and delivery of software solutions across one or more small, high‑velocity engineering teams. This role operates above the Software Engineer level and blends deep engineering excellence with a modern AI‑first mindset — including the ability to rapidly prototype with tools like Claude, Amazon Bedrock, and other GenAI platforms to accelerate team output and innovation.

• Develop and review architectural and technical design decisions for features, services, or platforms.
• Decompose epics and features into technical implementation plans with clear ownership.
• Review and approve technical designs, code changes, and pull requests
• Identify technical risks, dependencies, and trade-offs; propose mitigation strategies.
• Drive root‑cause analysis and resolution of complex production issues.

• Design, develop, test, and deploy full‑stack applications across the core stack:
  React / Type Script (web), Flutter / Dart (mobile & cross‑platform), and Python / Node.js (backend).
• Build and maintain scalable REST and GraphQL APIs using AWS API Gateway + Lambda.
• Implement CI/CD pipelines, infrastructure‑as‑code (AWS CDK / SAM), and blue/green deployment strategies
• Ensure production readiness through observability, automated testing, and monitoring
• AWS Serverless Architecture (Core Competency)
• Lead design and delivery of event‑driven, serverless‑first architectures on AWS.
• Deep hands‑on expertise across:
  • Compute:
    Lambda, Step Functions
  • Data:
    DynamoDB (primary), S3, Aurora Serverless
  • Messaging & Events: SQS, SNS, Event Bridge
  • API & Auth: API Gateway, Cognito, App Sync
  • Observability:
    Cloud Watch, X‑Ray
  • Infrastructure as Code: CDK, SAM, Cloud Formation
• Also responsible for cloud cost optimization, security posture, performance tuning, and defining serverless design patterns and guardrails for the team.

• Rapidly prototype new product concepts using Claude, Amazon Bedrock, and other LLM/GenAI platforms.
• Apply AI‑assisted development tools to accelerate code generation, testing, documentation, and code review.
• Evaluate AI-generated outputs for correctness, security, and production readiness.
• Define team‑level standards and best practices for AI tool adoption.
• Demonstrate ability to ideate → prototype → validate → ship in tight cycles to support fast‑moving engineering teams.

• Serve as the technical anchor for a small, high‑velocity scrum team — guiding direction, coaching engineers, and driving accountability.
• Partner with Product Managers, Architects, and QA to align technical direction with organizational goals.
• Mentor mid‑level, and junior engineers on design, cloud practices, and AI tool usage.
• Promote a culture of quality, continuous improvement, and learning.

• 6+ years of professional software engineering experience.
• Across web (React/Type Script), mobile/cross‑platform (Flutter/Dart), and backend (Python or Node.js):
  True full‑stack fluency.
• Lambda, DynamoDB, API Gateway, SQS/SNS, Event Bridge:
  Minimum 2 years of hands‑on AWS serverless experience.
• Demonstrated experience with using CI/CD, infrastructure‑as‑code, and serverless deployment patterns.
• Proven track record of rapid prototyping with AI/GenAI tools in a professional setting.
• Experience leading technical initiatives and mentoring small engineering teams.
• Understanding of prompt engineering, context management, and AI tool limitations.
• Availability…