We are partnering with a fast-growing technology startup building an AI-native enterprise platform designed to transform how organizations analyze, search, and interact with complex business documents. The platform leverages large language models, retrieval-augmented generation (RAG), semantic search, and modern cloud infrastructure to help knowledge workers extract insights, automate document workflows, and make faster, more informed decisions. As the product evolves from early production to large-scale adoption, the engineering team is investing heavily in building a highly scalable, secure, and maintainable platform capable of serving enterprise customers. The founding team has extensive experience building and scaling technology companies and is assembling a world-class engineering organization focused on technical excellence, product quality, and long-term platform architecture.

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Role and Responsibilities

• Own the design, development, and evolution of backend services while contributing across the full-stack when needed.
• Build scalable backend systems using modern Python and Go architectures.
• Design, implement, and maintain high-performance REST APIs and asynchronous services following API-first development practices.
• Transform existing proof-of-concepts into production-ready, scalable, and maintainable software components.
• Design and optimize relational and vector-based data storage strategies for structured data, semantic search, and AI-driven retrieval.
• Collaborate closely with AI engineers to build retrieval pipelines, indexing systems, and model orchestration services that power intelligent product capabilities.
• Partner with frontend engineers to deliver reliable, well-documented APIs and seamless product experiences.
• Work closely with Product and Design teams to translate business requirements into scalable technical solutions.
• Design secure authentication, authorization, and multi-user access models following enterprise security best practices.
• Build highly observable systems using structured logging, monitoring, distributed tracing, and performance metrics.
• Improve application performance, scalability, and reliability across backend services and data pipelines.
• Contribute to CI/CD pipelines, deployment automation, infrastructure improvements, and engineering productivity initiatives.
• Participate in architecture discussions, technical documentation, code reviews, and engineering best practices.
• Help establish the long-term technical foundation of an AI-first enterprise SaaS platform.

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What We're Looking For

Must-Haves

• 4+ years of professional software engineering experience with strong backend development expertise.
• Strong experience building production systems using Python.
• Professional experience with Go (Golang) or willingness to work extensively with Go-based services.
• Experience building scalable RESTful APIs and asynchronous backend architectures.
• Strong understanding of modern software architecture, distributed systems, and scalable backend design.
• Experience working with PostgreSQL or other relational databases.
• Familiarity with vector databases or semantic search technologies.
• Experience with asynchronous processing, background jobs, caching, and event-driven architectures.
• Experience deploying containerized applications using Docker and cloud-native infrastructure.
• Familiarity with Kubernetes and modern cloud platforms.
• Strong understanding of authentication, authorization, API security, and enterprise software best practices.
• Experience implementing automated testing, CI/CD pipelines, and production observability.
• Strong communication skills and ability to collaborate effectively within cross-functional engineering teams.
• Comfortable working in startup environments with high ownership, ambiguity, and rapid product iteration.

Nice-to-Haves

• Experience building AI-powered products or integrating LLM-based capabilities into production systems.
• Familiarity with Retrieval-Augmented Generation (RAG), embeddings, semantic search, or vector search architectures.
• Experience with Temporal, message queues, workflow orchestration, or distributed task processing.
• Experience working with OpenTelemetry, Prometheus, Grafana, or modern observability platforms.
• Experience with GitHub Actions, ArgoCD, or GitOps deployment workflows.
• Exposure to multi-tenant SaaS architectures and enterprise-scale software platforms.
• Experience optimizing high-throughput backend services for performance and reliability.
• Startup or early-stage product development experience.
• Strong interest in AI infrastructure, platform engineering, and scalable distributed systems.

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Preferred Technical Stack

• Python
• Golang
• FastAPI
• PostgreSQL
• Vector Databases (Qdrant or similar)
• Redis
• Docker
• Kubernetes
• GitHub Actions
• ArgoCD
• OpenTelemetry
• Prometheus
• Grafana
• REST APIs
• OpenAPI
• Async Processing
• Cloud Platforms (AWS, GCP, or Azure)

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Why Join Us?

• Build the core platform powering an AI-native enterprise product with significant technical challenges.
• Work alongside experienced engineers building cutting-edge AI infrastructure and enterprise software.
• Influence architecture, engineering standards, and long-term technical direction from an early stage.
• Solve complex distributed systems, scalability, search, and AI integration problems.
• Collaborate in a remote-first engineering culture built around ownership, autonomy, and technical excellence.
• Opportunity to grow into Staff Engineer, Principal Engineer, or Engineering Leadership roles as the company scales.
• Join a fast-moving team focused on delivering meaningful customer impact through modern AI technologies.

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Application Instructions

Please send the following and we will contact you:

• Your résumé/CV highlighting relevant backend or full-stack engineering experience.
• Links to GitHub, portfolio, technical blog, or other relevant work samples.
• Your availability and expected compensation.
• Brief description of the most technically challenging backend or distributed system you have built and your specific contributions.
• Any experience with AI platforms, RAG systems, cloud-native infrastructure, or startup environments you would like to highlight (optional but highly valued).