Website:
trustlogix.ai
Job details:
Overview: We are seeking a passionate, AI-First Software Architect to join the startup building innovative, AI-driven cloud-native data protection solutions. You must be comfortable designing scalable architectures that integrate generative AI securely, scoping complex cloud security requirements, and building robust systems from the ground up. This is a phenomenal opportunity for an architect willing to step out of their comfort zone, embrace AI-native paradigms, and solve high-impact, modern data and agentic security concerns.
Desired Background and Experience:
- Problem-Solving Mindset: Must be a relentless problem solver with an AI-first approach to software design.
- Core Engineering Experience: Minimum of 15 years of experience building scalable products. Deep expertise in Python (critical for AI/ML ecosystems) and/or Java. Prior work in startups is a huge plus.
- AI & API Architecture: 6+ years of experience building robust REST APIs and microservices (using Spring Boot, FastAPI, etc.), with a strong emphasis on integrating AI models, LLMs, and agentic workflows.
- GenAI & LLM Frameworks: Strong hands-on experience with GenAI frameworks and managed AI tools (e.g., AWS Bedrock, LangChain, LlamaIndex, OpenAI APIs).
- Modern Data & Vector Ecosystems: 8+ years of experience working with SQL databases and modern data warehouses (Snowflake, Databricks, AWS Redshift). Experience with or strong interest in Vector Databases (e.g., Pinecone, Milvus, pgvector) for Retrieval-Augmented Generation (RAG) is highly desired.
- Containerization & MLOps: 6+ years of experience developing and deploying Docker-based containers in production. Familiarity with deploying AI models or MLOps pipelines is a strong advantage.
- Cloud Platforms: Extensive familiarity with various cloud providers (AWS, Azure, GCP) and their native AI/ML managed services (e.g., AWS Bedrock, Azure AI Foundry).
- AI Data Security: Proven data security experience in highly regulated domains (Finance, Banking, Healthcare, etc.). Must understand the security implications of AI (e.g., prompt injection, data privacy, governance, and secure LLM guardrails).
- Frontend Exposure: Exposure to modern UI frameworks like React JS and TypeScript to help build intuitive, AI-assisted user experiences.
- Rapid Prototyping: Highly comfortable with rapid prototyping of AI features and fast-paced product implementation in an agile environment.
- Systems Engineering: Strong systems engineering experience, particularly in designing scalable data pipelines, RAG architectures, and secure API access controls.
- Design Patterns: Deep knowledge of cloud-native design patterns and emerging AI application architectures.
- Customer Empathy & Support: Must be able to provide technical support and guidance to customers deploying our solutions across different time zones.
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