Inbenta AI needs Full Stack engineers with significant backend experience specializing in data automation, optimization, security, and building AI-driven backend engines to shape the reliability, scalability, and security of their systems.
Requirements
- Strong Python and TypeScript (Next and Node.js) skills and hands-on experience with PostgreSQL optimization (NLP experience desired).
- Proven track record in backend security (auth, RBAC, secure API design, encryption).
- Experience deploying in modern cloud/serverless environments (AWS, GCP, AZURE).
- Hands-on experience with LLM frameworks (LangChain, AutoGen, ReAct-style orchestration) - either in production systems or through personal projects/demos.
- Experience with vector databases (Pinecone, Weaviate, Qdrant).
- Redis for caching, queues, pub-sub.
- Prisma or Drizzle ORM.
Responsibilities
- Build secure, production-grade applications and automations that interact with LLMs and agent frameworks.
- Strengthen our systems with robust authentication, encryption, and compliance practices.
- Architect APIs and backend flows for high reliability and efficiency.
- Help define product direction by shaping how our platform handles data, memory, and intelligence.
- Architect and implement end-to-end AI software solutions, from feasibility studies and prototyping to production-ready systems.
- Collaborate with data scientists to transition machine learning models from research/development into production environments using APIs and microservices.
- Conduct rigorous testing, debugging, and performance optimization of AI models and applications, and implement continuous monitoring (MLOps) to ensure scalability and reliability.
Other
- 7+ years of Full Stack engineering experience (with at least 2 years in data/security-heavy environments).
- Collaborate directly with founders and engineers to bring ambitious ideas to life.
- Work closely with cross-functional teams (e.g., data scientists, product managers, business stakeholders) to define AI product features, align on goals, and communicate complex technical concepts to non-technical audiences.
- Stay current with the latest AI advancements and emerging technologies (e.g., Generative AI, LLMs) and recommend new strategies or improvements to existing systems.
- Comfortable working in fast-paced, high-energy environments.
