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We are looking for a versatile Backend Software Engineer to own the design, development, and maintenance of Archer’s internal tooling ecosystem. In this role, you will act as a force multiplier for the entire organization—from Hardware Engineers analyzing flight data to Talent Acquisition teams scaling our workforce. You will not just be writing code; you will be solving complex workflow problems. You will be responsible for deploying Generative AI solutions, building data-intensive platforms, and automating critical business operations.
Job Responsibility:
Design, develop, and maintain scalable backend systems and APIs for internal tools supporting engineering, manufacturing, supply chain, and business operations
Build automation tools and workflows that streamline cross-functional processes
Implement robust data pipelines and integration systems connecting various internal platforms
Ensure code quality through comprehensive testing, code reviews, and adherence to engineering best practices
Design and manage cloud infrastructure with a focus on scalability, reliability, and security
Monitor system performance, troubleshoot issues, and optimize for efficiency
Establish infrastructure as code practices and maintain version-controlled configurations
Partner with multidisciplinary stakeholders including engineers, operations teams, program managers, and executives to understand requirements and deliver solutions
Translate business needs into technical specifications and architectural designs
Requirements:
4+ years of professional backend engineering experience
Strong proficiency in at least one backend programming language (Python, Go, Java, Node.js, or similar)
Extensive experience with cloud platforms (AWS, GCP, or Azure) and cloud-native architecture
Solid understanding of DevOps principles with hands-on experience in: CI/CD tools (TeamCity, Jenkins, GitLab CI, GitHub Actions, CircleCI, etc.)
Containerization and orchestration (Docker, Kubernetes, Prefect/Airflow)
Infrastructure as Code (Terraform, CloudFormation, Ansible, etc.)
Proficiency with relational and NoSQL databases
Experience with RESTful API design and microservices architecture
Strong understanding of software engineering best practices including version control, testing, and code review
Proven ability to work effectively with cross-functional teams and non-technical stakeholders
Knowledge of observability tools (Prometheus, Grafana, DataDog, etc.)
Excellent problem-solving skills and attention to detail
Strong written and verbal communication skills
Nice to have:
Bachelor's degree in Computer Science, Engineering, or related field (or equivalent experience)
Background in building internal developer tools or platforms
Hands-on experience integrating Gen AI via API and a familiarity with employing RAG in custom applications
Experience with message queuing systems (RabbitMQ, Kafka, etc.)
Experience with GraphQL APIs
Familiarity with data warehousing and analytics platforms
Experience building with Model Context Protocol (MCP) servers to connect data sources to LLMs