Turing - Lead Forward Deployed Fullstack Engineer

• Full-Stack Engineering (Primary) • 10+ years of hands-on software development, with deep expertise in modern Java full-stack development. • Strong command of Java frameworks including Spring, Spring Boot, and Hibernate. • Proven experience building single-page web applications using ReactJS, Bootstrap, and Node.js. • Solid understanding of front-end architecture principles and data-driven UI development. • Hands-on experience designing, developing, and deploying cloud-based architectures on AWS or Azure — not inherited pipelines, genuine architecture ownership. • Expertise developing applications backed by both relational (SQL Server/PostgreSQL) and NoSQL (MongoDB/Elasticsearch) databases. • Strong SQL development skills including query optimization and performance tuning. • Working knowledge of modern security frameworks and standards: OAuth 2.0, OpenID Connect, and JWT. • Proficient in designing and building RESTful APIs following industry best practices. • Experience with modern testing frameworks (Jest, Mocha, Chai) and a commitment to test-driven development. • Demonstrated ability to write clean, efficient, maintainable code across a diverse stack. • Excellent problem-solving and troubleshooting skills for diagnosing complex technical issues. • Polyglot Engineering • Comfortable working across multiple languages and tech stacks — not single-stack only. • Solid hands-on experience developing production applications, automation tooling, or backend services in Python. • AI / Agentic Integration (Secondary, But Important) • We are not looking for candidates who only exist in Python or whose entire background is LLM/model training. We are looking for full-stack engineers who have demonstrably built systems with AI components — or who have the depth and drive to take that on. • Practical experience integrating LLMs into applications via APIs (e.g., OpenAI, Anthropic Claude, Azure OpenAI, AWS Bedrock). • Ability to add AI capabilities on top of existing enterprise systems — examples include invoice OCR with LLM-based data extraction, validation against contracts, and payment logic. • Familiarity with prompt engineering, Retrieval-Augmented Generation (RAG), embeddings, and vector databases. • Understanding of responsible AI practices: data privacy, hallucination mitigation, evaluation, and guardrails. • Willingness and ability to grow into deeper agentic/LLM work over time. • Proven ability to lead, mentor, and grow engineering teams — with genuine ownership of that role, not circumstantial seniority. • Experience driving architectural decisions and setting technical direction across cross-functional teams. • Strong stakeholder management: able to translate business requirements into scalable technical solutions. • Track record of leading end-to-end delivery of complex projects from design through deployment. • Effective communicator with both technical and non-technical audiences. • Skilled at conducting code reviews, establishing best practices, and raising the bar for code quality. • Experience coaching junior engineers, contributing to hiring, and managing technical debt alongside delivery pressures. • Ownership mindset — takes accountability for outcomes and drives initiatives forward proactively. • Good to Have (Palantir Foundry) • Hands-on experience with Palantir Foundry including pipelines, ontologies, and data-driven applications. • Familiarity with Foundry's development tooling: PySpark transforms, TypeScript-based Functions, Workshop. • Exposure to enterprise-scale data integration and operational analytics workflows on Palantir. • Exposure to AI/ML frameworks such as LangChain, LlamaIndex, or Hugging Face. • Ability to identify and apply AI-driven solutions to real-world business problems within enterprise systems.