Senior Software Engineer, SponsorUnited

• 8+ years of professional experience in software engineering with a full stack focus
• Deep expertise in cloud platforms (AWS, GCP, or Azure)
• Proficient with containerization (Docker) and orchestration (Kubernetes) for microservices
• Hands-on experience with CI/CD tools (Jenkins, GitHub Actions, CircleCI) and GitHub workflows
• Strong proficiency in Python (FastAPI) and TypeScript (Angular)
• Solid understanding of webhooks, websockets, and real-time communication patterns
• Extensive experience with relational (PostgreSQL) and NoSQL (DynamoDB) databases; familiarity with graph databases is a plus
• Experience with vector databases (Chroma, Pinecone, etc.) for AI/ML use cases
• Proven track record implementing OAuth 2.0 or similar authentication/authorization frameworks
• Demonstrated ability to deliver secure, high-performing, and scalable web applications
• Experience working with state-of-the-art AI/ML frameworks. LangChain, LangGraph, or LangSmith is a plus
• Advanced understanding of code quality, testing (unit, e2e, evaluation), and modern best practices in software development
• Excellent communication skills, collaborative mindset, and strong problem-solving abilities

Desirable

• SponsorUnited is seeking a Senior Software Engineer-(AI/GenAI Solutions Architect) to drive innovation in AI-powered automation and data extraction across our platform
• This role goes beyond implementation—you will architect, prototype, and lead the development of cutting-edge AI/GenAI solutions, with a focus on agentic workflows, automated data pipelines, and rapid experimentation
• You will work cross-functionally to transform concepts into production-ready tools and processes that scale, while staying current on evolving AI/ML trends and technologies
• As a technical leader, you will help shape SponsorUnited’s AI roadmap, mentor engineers, and champion emerging technologies across the organization
• AI/GenAI Architecture & Prototyping
• Architect and prototype AI-driven systems focused on automated data extraction, agentic workflows, and LLM orchestration
• Rapidly experiment with frameworks like LangChain, LangGraph, and LangSmith, and llms like OpenAI, Anthropic, and Gemini api solutions to validate ideas and accelerate deployment
• Design and direct the implementation of retrieval-augmented generation (RAG) pipelines, chunking strategies, and autonomous agent systems
• AI Integration:
• Integrate and deploy AI solutions, including RAG (Retrieval-Augmented Generation) and chunking techniques for large language models
• Leverage frameworks such as LangChain, LangGraph, LangSmith, or similar modern high-level AI libraries
• Database and Storage:
• Implement and optimize relational (PostgreSQL), NoSQL (DynamoDB), and graph databases for diverse data needs
• Utilize vector stores (Chroma, Zillis, etc.) to support AI-driven features
• Use Redis for caching and real-time data processing
• Tune queries and database structures for high-volume data ingestion and retrieval
• Microservices & Scalability:
• Design and deploy microservices architectures using Docker and Kubernetes
• Ensure services are highly available, scalable, and fault-tolerant
• Collaborate with DevOps to optimize CI/CD pipelines (Jenkins, GitHub Actions, CircleCI)
• Security and Authorization:
• Implement OAuth 2.0 and other secure mechanisms for user authentication and authorization
• Conduct regular security assessments, address vulnerabilities proactively, and adhere to industry best practices
• Testing & Quality Assurance:
• Drive testing best practices, including unit tests, integration tests, end-to-end (e2e) tests, and evaluation for AI components
• Collaborate with QA to ensure coverage across all features and regression scenarios
• Performance, Reliability & Monitoring:
• Use metrics, monitoring, and alerting systems to track performance, usage, and system health
• Troubleshoot, diagnose, and resolve production issues with minimal downtime
• Continuously improve logging and observability to enhance reliability
• Collaboration & Leadership:
• Work closely with Product, Design, and DevOps to translate business requirements into robust technical solutions
• Participate in code reviews, architectural discussions, and strategic technical decision-making