Full Stack AI Software Engineer

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

📋 Description

• Design, develop, deploy, secure, and continuously enhance enterprise software and AI-driven applications.

• Collaborate with business stakeholders to identify issues, define outcomes, and create technical solutions.

• Convert business requirements into detailed specifications, technical designs, user stories, acceptance criteria, and production-ready software.

• Quickly prototype, demonstrate, test with users, and iteratively release new functionalities.

• Create and improve applications across frontend, backend, API, integration, data, and infrastructure layers.

• Design reusable services, components, APIs, workflows, and integration patterns.

• Implement AI functionalities using large language models, retrieval-augmented generation, embeddings, vector search, structured outputs, tool calling, multimodal models, and agentic workflows.

• Develop secure AI agents that interact with applications, APIs, databases, documents, and enterprise systems.

• Create prompts, system instructions, context-management strategies, tool definitions, workflows, and reusable AI capabilities.

• Assess models and apply evaluations, regression testing, guardrails, human-review controls, grounding, observability, and fallback mechanisms.

• Identify and address hallucination, prompt-injection, data-leakage, model-bias, unsafe-output, and unauthorized-tool-use risks.

• Oversee software delivery from discovery and architecture through development, testing, deployment, production support, and ongoing improvement.

• Write clean, modular, testable, secure, and well-documented production code.

• Develop and maintain automated unit, integration, API, UI, regression, performance, security, and end-to-end testing.

• Build and manage CI/CD pipelines and release software through safe, observable, and reversible deployment practices.

• Act as the accountable engineer or technical owner for up to three applications.

• Monitor availability, performance, capacity, security, errors, and user experience; diagnose and resolve incidents and defects.

• Conduct maintenance, upgrades, vulnerability remediation, documentation, incident response, root-cause analysis, disaster-recovery testing, and business-continuity exercises.

• Recommend modernization, re-platforming, consolidation, or decommissioning of applications.

• Work closely with Information Security, Enterprise Architecture, database, data-management, IT Support, infrastructure, cloud, network, identity, DevOps, QA, product, legal, risk, and compliance teams.

• Communicate technical decisions, constraints, risks, trade-offs, progress, and recommendations to both technical and non-technical audiences.

• Adhere to software-development, change-management, security, architecture, data-governance, and release-management standards.

• Ensure compliance with legal, regulatory, privacy, records-management, accessibility, and industry standards.

• Safeguard confidential, proprietary, customer, and regulated data.

• Review, test, and appropriately license AI-generated code and content.

• Contribute reusable engineering patterns, libraries, templates, prompts, skills, standards, and lessons learned.

• Mentor other engineers and enhance AI-enabled software-delivery standards.

• Undertake other related responsibilities as assigned.

⛳️ Requirements

• A minimum of five years of professional software engineering experience encompassing the design, development, testing, deployment, and support of production applications.

• At least two to three years of professional experience in engineering software utilizing modern AI-assisted engineering tools and practices.

• Proven ability to create and support full-stack applications from initial concept to production.

• Strong proficiency in at least one modern backend programming language such as Python, Java, C#, Go, or TypeScript/Node.js.

• Strong expertise in modern frontend development with JavaScript or TypeScript and a framework like React, Angular, or Vue.

• Experience in designing and utilizing RESTful APIs, event-driven services, microservices, and enterprise integrations.

• Familiarity with relational databases, SQL, data modeling, and at least one modern non-relational or vector-database technology.

• Practical experience in integrating large language models or generative AI services into production or enterprise applications.

• Experience with AI coding tools such as Cursor, Claude Code, GitHub Copilot, OpenAI Codex, or similar platforms.

• Experience with Git-based source control, automated testing, code reviews, continuous integration, continuous delivery, and modern DevOps methodologies.

• Experience in deploying and managing applications in AWS, Microsoft Azure, or Google Cloud Platform.

• Working knowledge of containers, infrastructure as code, observability, application security, and vulnerability remediation.

• Strong understanding of secure software development principles, including authentication, authorization, encryption, secrets management, dependency management, and common application security risks.

• Demonstrated ability to work directly with business users to translate business challenges into functional software.

• Excellent analytical, troubleshooting, communication, collaboration, and documentation skills.

• Ability to independently manage multiple priorities while maintaining ownership of up to three applications.

• Bachelor’s or master’s degree in computer science, software engineering, information systems, data science, artificial intelligence, or a related field, or equivalent practical experience.

• Experience in building AI agents, retrieval-augmented generation solutions, semantic search applications, document processing systems, or workflow automation.

• Familiarity with model evaluation frameworks, prompt testing, AI observability, red team testing, and responsible AI controls.

• Experience with LangGraph, Semantic Kernel, OpenAI Agents SDK, model context protocol, or similar orchestration technologies.

• Experience with Kubernetes, serverless architectures, messaging platforms, API gateways, and distributed systems.

• Experience working in a regulated industry such as financial services, mortgage lending, banking, insurance, healthcare, or government.

• Experience modernizing legacy applications and integrating them with cloud, data, and AI platforms.

• Certificates, Licenses, Registrations: None Required.

• Ability to comply with company policies and maintain regular and punctual attendance.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health, dental, and vision insurance.

• Generous paid time off and holiday policies.

• Opportunities for professional development and career growth.

• Flexible work arrangements and a supportive work environment.