Independently build and deploy web or application features using one or more languages proficiently; make sound implementation decisions about code structure, error handling, and testability within the established architecture.
Write complex SQL queries independently; optimize performance, apply appropriate indexing and query patterns by workload, and write queries that are readable and maintainable.
Design and implement REST APIs and application services that are well-documented, versioned appropriately, and built to handle failure gracefully.
Write comprehensive unit and integration tests for developed features; treat testing as part of development, not a separate activity, and design code with testability in mind from the start.
Participate in code review as both reviewer and reviewee; apply feedback consistently, provide specific and actionable feedback to junior developers, and use review as a tool for shared code ownership.
Cloud and Infrastructure
Independently design and operate serverless and containerized compute architectures on AWS using Lambda, ECS, EKS, and related services; make platform decisions with awareness of cost, performance, and operational complexity.
Independently design and manage API Gateways and VPC configurations for production application workloads; understand networking fundamentals well enough to debug connectivity issues.
Independently build and manage CI/CD pipelines using AWS CodeSuite or equivalent; design pipelines that include testing gates, deployment validation, and rollback capability.
Configure comprehensive monitoring and alerting for production application systems; implement observability so failures are detected and triaged before they affect client outcomes.
Independently containerize applications and manage Kubernetes workloads in production environments; apply sound practices for resource allocation, health checking, and workload scaling.
LLM and AI Integration
Independently build LLM-powered application features; apply prompt engineering, manage model behavior and token budgets, and design AI interactions that are reliable and appropriate for production use.
Integrate RAG pipelines and vector search components into application layers; work with data scientists to ensure retrieval quality meets application requirements.
Leverage AI coding assistants to accelerate development, testing, and code review tasks; validate AI-generated code critically and apply it with the same engineering discipline as hand-written code.
Quality and Documentation
Write and maintain technical documentation for APIs, application components, and architectural decisions; document at the level of detail that enables a teammate unfamiliar with your work to use, maintain, and extend it.
Maintain high-quality code history; write commit messages, pull request descriptions, and changelogs that make the evolution of the codebase understandable.
Participate in architecture discussions and contribute well-reasoned technical opinions grounded in both current requirements and long-term maintainability.
Collaboration and Mentorship
Provide structured support to junior developers through hands-on coaching, code review, documentation, and pairing; help them develop the engineering habits and communication skills that will carry them toward independent contribution.
Collaborate with data engineers and data scientists to integrate data pipelines and model outputs into application layers; understand the full system well enough to design application code that works with data and ML constraints.
Partner with project managers to keep software delivery aligned with client expectations and contractual constraints; surface scope and timeline risks early with enough context for leadership to act.
Participate in sprint planning, retrospectives, and estimation ceremonies; manage work in Jira with accuracy and discipline and communicate progress and blockers proactively.
Qualifications
Required
Bachelor's degree in Computer Science, Software Engineering, or a related field.
3 to 5 years of hands-on software development experience, including production feature delivery with full lifecycle ownership.
Proficiency in one or more backend languages (Python, Java, TypeScript/Node.js, or Go) and familiarity with modern front-end frameworks such as React.
Hands-on experience with AWS services including Lambda, ECS/EKS, API Gateway, DynamoDB, RDS, and S3 for production application workloads.
Experience with CI/CD pipeline design and implementation, version control workflows, and containerization using Docker.
Demonstrated ability to write clean, tested, production-grade application code with appropriate observability and error handling.
Strong written and verbal communication skills; able to collaborate effectively across technical and analytical disciplines and document work clearly.
Preferred
AWS Developer Associate or Solutions Architect Associate certification.
Experience with infrastructure-as-code tools such as Terraform or CDK.
Experience integrating LLM API endpoints, RAG pipelines, or AI service components into production applications.
Familiarity with Kubernetes cluster management and production container orchestration.
Background in consulting, professional services, or multi-client delivery environments.