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12 days ago
Requirements and responsibilities
The Senior Application Engineer designs and builds resilient software for complex internal applications, with a focus on API development, data services, and cloud-based infrastructure. The role integrates AI capabilities into the product suite and uses AI development tooling and AI DevOps practices to build, iterate, govern, and scale applications with greater speed and quality—accounting for AI’s strengths and failure modes. Day-to-day work spans a modern JavaScript frontend, a server-side language such as PHP or Python, and AWS infrastructure.What You'll Do Every DaySystem Design & Development: Collaborate in designing and building resilient, AI-integrated software for complex internal applications, with emphasis on API development, data services, and cloud infrastructure.AI-Integrated Application Development: Build and maintain AI-powered features within internal applications by integrating APIs from providers such as OpenAI, Anthropic, and Google; scope, implement, and harden LLM-connected capabilities through testing and production deployment.Coding and Development: Write and manage application code, scripts, and automations using JavaScript, Python, and PHP; design and maintain serverless Cloud Functions on AWS with emphasis on performance, reliability, and clean integration with AI-driven workflows.Database Management: Manage data using MySQL and PostgreSQL; ensure scalability, reliability, and security for databases supporting both traditional and AI-enhanced application layers.Problem-Solving: Identify and resolve complex technical issues, including those specific to AI integration, model behavior, and API reliability, independently and collaboratively.Documentation & Reporting: Maintain clear, precise documentation of code, AI workflows, system behaviors, and processes.AI-Powered Development & DevOps: Use tools like Claude Code, Cursor, GitHub Copilot, and AI-enabled CLI utilities across the development lifecycle to accelerate coding, code review, debugging, and testing; champion AI DevOps practices such as automated pipelines, AI-assisted testing, deployment tooling, and performance monitoring; evaluate emerging tools and establish standards for responsible use across the SDLC.Implementation Oversight: Lead implementation by overseeing code quality and performing reviews; optimize application performance in cloud environments, focusing on efficient use of AWS services, SQS handling, and automated testing.Projects & Teammate Mentorship: Provide mentorship and guidance on AI integration approaches, development tooling, and application architecture; offer project consultation to uphold and advance engineering standards.Additional duties, as assigned.Requirements4+ years of professional software engineering experience, with a track record of shipping and maintaining production systems (exemplary performance may supersede the experience requirement).Strong computer science fundamentals: data structures, algorithms, time/space complexity, and object-oriented and functional design patterns; ability to apply across languages.Experience integrating third-party APIs (including generative AI providers like OpenAI, Anthropic, or Google) into production, including rate limits, retries, idempotency, schema design, and failure modes.Proficiency with AI-powered development tools such as Claude Code, Cursor, GitHub Copilot, or equivalent CLI and agentic coding tools as part of a professional engineering workflow.Familiarity with AI DevOps practices across the SDLC for code review, automated testing, deployment pipelines, and application monitoring.Solid experience with SQL for data manipulation and analysis (data tools like Pandas are a plus).Ability to build, deploy, and manage applications in cloud environments, specifically AWS.Experience designing and implementing well-structured APIs for data integration across systems, with fluency in at least one paradigm (REST, GraphQL, gRPC, or event-driven/messaging) and understanding of when to use each.Experience working with structured data and running extract, load, and transform (ETL) processes.Strong debugging and systems-thinking skills across client/service/data/infra layers, including non-deterministic behavior in AI-integrated systems.Effective communication skills, including ability to break down technical concepts for non-technical stakeholders.BenefitsHigh-character, fun, and cohesive work cultureCompetitive base salaryPTO that is genuinely encouragedAffordable, low-deductible health insurance plansSupplemental benefits including employer-paid life insurance, short & long term disability insurance401k with company matchRemote work flexibilitySupportive, transparent, and accessible leadershipProfessional/individual development stipendSalary Description: $95,000-$120,000Work Authorization/RequirementsMust be located in the USA.Unable to sponsor or take over sponsorship of an employment Visa at this time.
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