Position Tittle: Python/VueJS with AI-Software Engineer
Location: 100% remote
Duration: Long Term
Job Details:
We are seeking a high-caliber Senior Software Engineer to join a team building customer-centric solutions for the business. This role is designed for a top-tier engineer who combines deep technical expertise with strong product intuition and business acumen. You will tackle ambiguous challenges, rapidly prototype solutions directly with stakeholders, and architect scalable, secure systems. You operate with high autonomy, acting as the critical technical bridge that turns business objectives into high-performing software.
Enterprise Req Skills
Python,vue.js,aws,google cloud platform,terraform,api,Development,Agile,Software development,Cloud,Linux
Top Skills Details
Required Qualifications
• Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.
• 9+ years of experience designing, supporting, and deploying modern, enterprise-grade software systems.
• Skilled at using agentic AI tools throughout the SDLC.
• Hands-on expertise with technologies such as Python, Vue.js, AWS/Google Cloud Platform cloud platforms, Terraform, APIs, and cloud-native architecture patterns.
• Proven ability to interact directly with business stakeholders, build trust, and operate autonomously in fast-paced environments.
External Communities Job Description
We are seeking a high-caliber Senior Software Engineer to join a team building customer-centric solutions for the business.
EVP
Work on cutting edge technology that will bring AI efficiencies to the business
Additional Skills Tags
Software development,Cloud,Linux
Additional Skills & Qualifications
1. Engineering & System Design
• Architect in Ambiguity: Translate loosely defined business problems into clean, robust architectures while anticipating edge cases.
• Rapid Prototyping[GB1.1][SC1.2]: Where applicable, build functional prototypes with stakeholders to validate ideas instantly and accelerate the feedback loop.
• Full-Stack Delivery: Own features end-to-end across services, data, and UI, making pragmatic technology choices and avoiding unnecessary complexity.
2. Engineering Productivity with AI[GB2.1][SC2.2]
• AI-Assisted Development: Use agentic AI tools throughout the SDLC to move faster, while maintaining full accountability for code quality, correctness, and security.
• Feedback Loops for Coding Agents: Design quality gates, spec-driven workflows, and deterministic checks that catch agent errors before humans do.
• Critical Adoption: Evaluate AI tools and patterns critically, adopting what improves the team\''''s output and discarding what doesn\''''t.
3. Reliability & DevSecOps
• Security-First Mindset: Embed security and compliance into the core of the development lifecycle, proactively mitigating vulnerabilities through secure design.
• Production Standards: Build well-tested, maintainable software. Implement CI/CD pipelines to ensure systems are resilient, scalable, and optimized for an exceptional end-user experience.
• Operational Readiness: [GB3.1]Make production behavior measurable, debuggable, and recoverable by building observability, alerting, runbooks, and recovery paths into systems from the start.
4. Execution & Business Ownership
• Drive Outcomes: Take ownership of delivering meaningful business results, managing scope responsibly, and communicating technical risks early.
• Technical Translation: Partner closely with Product Managers and business leaders. Articulate complex architectural decisions and tradeoffs in clear, outcome-oriented terms.
• Partnering Across Functions: [GB4.1][GB4.2]Engage security, risk, compliance, and platform teams
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