Software Engineering Consultant

Job Summary The Software Engineering Consultant is a backend-focused role with hands-on data platform and large language model (LLM) experience. This consultant will design, build, and deploy scalable services and integrations for business-critical applications. Success requires strong Python skills, production-ready coding standards, and effective collaboration in a client-facing consulting environment. Key Responsibilities Design and build backend services and REST APIs using Python (FastAPI, Flask, Django); occasional Node.js/TypeScript as needed Develop distributed microservices with token-based authentication and role-based access controls Integrate applications with third-party systems, external APIs, and Snowflake for data access and transformation Build LLM-powered features including model APIs, prompt workflows, structured outputs, and retrieval-augmented generation (RAG) applications Write secure, modular code with unit, integration, and automated tests Participate in Git workflows, code reviews, and CI/CD pipelines Troubleshoot application issues across integrations, data, and production environments Collaborate with teams to translate requirements into implementation plans and technical documentation Required Qualifications 35 years of software development or consulting experience Strong Python proficiency with at least one framework (FastAPI, Flask, Django) Working knowledge of Node.js/TypeScript Solid grasp of REST API design, microservices, authentication, and service-to-service integration Experience with Git workflows, CI/CD, and automated testing Hands-on Snowflake experience (data migration, querying, app integration) Proficiency integrating LLMs via hosted model APIs or enterprise AI platforms Strong debugging, communication, and problem-solving skills Preferred Qualifications Experience in consulting environments with client-facing responsibilities Background in enterprise data platforms or AI-driven applications Familiarity with cloud infrastructure and containerization (Docker, Kubernetes) Certifications None required; cloud or AI certifications (AWS, Google Cloud Platform, Azure, or AI/ML specialization) preferred Education: Bachelors Degree