Senior Full-Stack AI Engineer

SPD Technology is a global software product development company specializing in fintech, digital payment solutions, data engineering, AI/ML, and cloud technologies. Founded in 2006, it has delivered over 460 custom projects for startups, SMBs, and enterprises worldwide, including Fortune 500 firms. The company partners with industry leaders such as PitchBook, Morningstar, and Blackhawk Network, supporting clients that generate over $4B in annual revenue. SPD Technology has over 650 engineers across 35 countries and emphasizes high performance, accountability, and a flexible work environment.

• 5+ years of full-stack engineering experience with proven ability to design, deploy, and operate software in production independently.
• Expertise refactoring unorganized scripts, legacy code, or prototypes into maintainable production systems.
• Deep proficiency in Python (preferably FastAPI) and modern TypeScript/JavaScript frameworks (Vue.js or React).
• Hands-on experience with AWS infrastructure and Infrastructure as Code tools (Terraform, AWS CDK).
• Production experience with agentic AI frameworks including LangChain, LangGraph, tool integration, RAG, multi-agent orchestration, and error recovery.
• Solid understanding of CI/CD with GitHub Actions, containerization (Docker, Kubernetes), and modern AI developer tools (Cursor, Claude Code, Windsurf).
• Ability to deliver with high autonomy without dedicated QA, DevOps, or SRE teams.
• Strong system design skills, knowledge of distributed systems, relational and NoSQL database design, design patterns, and enterprise security standards.

Primary Responsibilities:

• Transform CTO Office proofs of concept, scripts, and experimental solutions into scalable production applications.
• Own projects end-to-end including discovery, system architecture, deployment, support, and improvements.
• Collaborate with CTO Office, FinOps, operations, sales, and pre-sales to translate business requirements into technical designs.
• Develop responsive frontends, robust Python backends, APIs, system integrations, and automated workflows using AWS serverless and containerized services.
• Engineer advanced AI workflows using LangChain, LangGraph, RAG, tool calling, multi-agent orchestration, custom MCP servers, and internal AI capabilities.
• Implement CI/CD pipelines with GitHub Actions, infrastructure as code, automated testing, logging, monitoring with CloudWatch and ELK Stack, and failure recovery.
• Manage production security including authentication protocols (OAuth 2.0, SAML, JWT), secret storage, certificates, and access controls.
• Define engineering standards, document systems clearly, and communicate risks and trade-offs transparently.