Senior Software Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Design, develop, and implement intricate technical solutions, including AI-enabled and agentic systems, that fulfill functional, performance, and security specifications.

• Create production-quality agents and AI-driven workflows that involve tool usage, orchestration, retrieval, and integration with record systems.

• Convert loosely defined business and product requirements into detailed technical plans and execute them effectively.

• Write maintainable and testable code, taking ownership of components from design through to production.

• Regularly utilize AI coding assistants and agentic coding tools to enhance team AI practices.

• Develop evaluation, testing, and observability measures for deployed AI behavior.

• Leverage AI throughout the processes of discovery, requirements gathering, building, testing, releasing, and supporting, while assessing the impact on speed and quality.

• Create secure interfaces, adapters, and guardrails for agents interacting with legacy systems.

• Engage in code and design reviews.

• Collaborate with product, architecture, QA, and DevOps teams to ensure end-to-end delivery quality and adherence to CI/CD practices.

• Identify technical and AI-related risks, including those pertaining to security, privacy, cost, and reliability.

• Assess emerging models, tools, and techniques, providing recommendations for suitable solutions.

• Work across Licensing, Registrations, Reservations, and other emerging product domains as priorities evolve.

⛳️ Requirements

• Must be a US Citizen or a Green Card holder.

• At least 7 years of hands-on software engineering experience, demonstrating ownership of significant components or features from design to production.

• A current, highly agentic working style, with AI coding agents integral to development and a capability to validate their output.

• Experience in building agents, automation processes, or tools such as custom agent workflows, MCP servers, or scripts that chain models and tools; side projects and internal tools are acceptable.

• Working knowledge of tool usage, orchestration, context management, and structured outputs.

• A practice of verifying AI output through testing, reviews, or lightweight evaluations.

• Understanding of AI security and data handling risks, including prompt injection, data leakage, and agent access control.

• A strong foundation in at least one modern programming language and the ability to quickly learn others.

• Familiarity with RESTful APIs, service-oriented or microservice architectures, and experience with at least one major cloud platform such as Azure, AWS, or GCP.

• Experience with relational databases and data modeling.

• Proficiency in DevOps practices and CI/CD tooling, encompassing automated build, test, and release pipelines.

• Experience working with or integrating into legacy and long-standing systems.

• No specific industry background is mandated.

• Preferred: Experience with LLM-powered product features, retrieval-augmented generation, evaluations, production AI monitoring, and vector or search stores.

• Preferred: Knowledge of Docker, Kubernetes, MCP or similar standards, modern front-end frameworks, open-source contributions, or technical writing skills.

🏝️ Benefits

• Health insurance, with certain plans fully covered for the employee (family members can be added at a discounted rate).

• Vision insurance fully covered for the employee (family members can be added at a discounted rate).

• Dental insurance available for purchase.

• Flexible/open paid time off (PTO) policy (available after 30 days of continuous service).

• Nine (9) paid holidays.

• 401(k) plan with matching contributions from the company.

• Annual year-end performance bonus (3.5% target).

• Up to 8 weeks of paid parental leave.

• Life insurance fully covered by the company.

• Long-term disability insurance fully covered by the company.

• Free Udemy account for ongoing professional development and learning.

• In-house AI training sessions conducted by notable system thinkers within the organization.