GoLang Software Engineer

Fynbosys — United States · Posted ~2 hours ago

Junior Full-time

Skills

Go Python microservices serverless applications API design DevOps cloud-native development serverless APIs

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Summary ✨ AI‑Generated

A software engineering position focused on building cloud-native solutions, microservices, and serverless applications. Engineers will develop clean code, collaborate across teams, and apply modern development practices.

Highlights

Offers mentorship, modern cloud-native development experience, AI-assisted engineering workflows, and opportunities to build impactful solutions.

Description

Software EngineerAs an Software Engineer, you will begin your career building modern, cloud-native solutions that directly impact our customers' supply chain operations. You will work within cross-functional teams to develop microservices and serverless applications, learning industry best practices while contributing to our platform transformation from legacy systems to a composable, MACH-based architecture. In this role, you will write clean, testable code primarily in GoLang and Python, participate in code reviews, and develop skills in cloud-native development patterns. You will collaborate with experienced engineers who will mentor you in serverless architectures, API design, and modern DevOps practices. You will use AI coding assistants (GitHub Copilot, Claude Code, Cursor, or equivalent) as a standard part of your daily development workflow — writing prompts, reviewing AI-generated output critically, and applying enterprise security controls to ensure production-quality results. You will build scalable, observable systems that meet enterprise-grade reliability standards and contribute to the team’s growing AI-native engineering practices. Your responsibilities will include owning complex technical deliverable, driving incident retrospectives, and ensuring solutions meet our reliability and scalability targets. You will collaborate closely with Senior Engineers, architects, and product leadership to align technical decisions with business strategy. You will model a culture that values engineering excellence, scope discipline, and practical problem-solving—where “reliable, accurate, scalable, and trusted” takes precedence over theoretical perfection. You will apply AI-assisted development responsibly — validating AI-generated code against security and quality standards, participating in AI code reviews, and contributing to team practices that govern safe AI use across the SDLC. You will communicate technical concepts effectively to diverse audiences and build consensus across the organization. Basic Qualifications: · Bachelor's Degree in Computer Science or related technical field · At least 3 years of professional software development experience · Strong proficiency in GoLang, React, Python, gRPC · At least 1 years of experience with AWS cloud services and serverless architectures · Proven experience executing technical design and architecture decisions · Active, hands-on proficiency with AI coding assistants (GitHub Copilot, Claude Code, Cursor, or equivalent) as a core part of daily development work, including the ability to critically review AI-generated output for correctness, security, and production quality Preferred Qualifications: · 5+ years of professional software development experience · 3+ years of experience building enterprise-scale cloud-native platforms · Deep expertise with AWS serverless technologies (Lambda, Step Functions, EventBridge, AppSync) · Experience with MACH architecture principles and composable systems · Hands-on experience integrating AI/ML models or LLM-based APIs into production workflows, including prompt design, output validation, and applying OWASP Top 10 for LLMs security controls · Strong background in event-driven architectures and distributed systems · Experience with observability platforms, distributed tracing, and SRE practices · Track record of leading platform migrations or modernization initiatives · Expertise in infrastructure as code and GitOps practices · AWS Certifications (Solutions Architect Professional or Developer Professional) · Experience in logistics, transportation, or supply chain technology domains · Familiarity with AI governance concepts: human-in-the-loop review patterns, AI code review checklists, and responsible AI use standards within an engineering team · Experience with agentic workflow patterns or LLM orchestration frameworks (LangChain, AutoGen, or equivalent) as components of production platform services