Assembly Industries
Senior Backend Engineer – Automation & Platform Implementation
Rol remoto de Backend Engineering con fit claro de ubicación del candidato.
Publicado4 jul 2026
Países elegibles1 país aceptado
Señal de senioritySenior
Modelo de trabajoRemoto
Ubicaciones aceptadas para candidatos
Argentina
Resumen del rol
Senior Backend Engineer – Automation & Platform Implementation
Requisitos y responsabilidades
Contenido del rol extraído en secciones para revisar más rápido.
🧱 Platform Development & Backend Architecture
- Build, extend, and optimize Java-based microservices responsible for task execution, state management, and orchestration logic.
- Model and manage NoSQL document databases to track execution state, workflow metadata, and session/context persistence.
- Define internal API contracts, adapters, and connectors that enable modular integration with external APIs and customer deployments.
🧠 AI-Related Backend Engineering
- Implement production-ready infrastructure for data ingestion, document chunking, embedding indexing, and retrieval (RAG) pipelines.
- Architect backend services that support multi-step agentic flows, including context assembly, tool calls, and session memory.
- Turn product requirements for semantic search and AI assistant features into resilient, production-grade backend code.
🤖 Customer Implementation & Enablement (FDE Work)
- Deploy, configure, and customize the automation platform to meet specific customer use cases and business requirements.
- Connect external systems through custom sync pipelines, webhooks, and enterprise integrations (e.g., OAuth, ETL-style ingestion).
- Debug production issues across our stack and customer environments, capturing field insights to improve the core platform.
- Enhance platform observability by setting up robust tracing, execution visibility, and debugging tools for failed runs.
Core Backend Engineering
- 4–6 years of software engineering experience building resilient production backend systems and working with distributed architectures.
- Strong proficiency in Java, with deep experience developing scalable microservices, handling asynchronous jobs, retries, idempotency, and system failure modes.
- Experience with NoSQL document databases (e.g., MongoDB, Firestore, Couchbase) for state and metadata tracking.
Automation & AI-Aware System Experience
- Experience building or integrating workflow engines or enterprise automation systems (beyond one-off scripting).
- Working knowledge of Python for building integrations, tooling, and rapid prototyping.
- Solid understanding of LLM application structures, including embedding systems, vector search, retrieval mechanics, context windows, and agent/tool execution.
- Strong interest or hands-on experience in semantic search, RAG pipelines, or conversational AI backends.
Professional Execution & Mindset
- High Agency & Independent Execution: You have a strong sense of ownership and the exceptional self-direction required to navigate undocumented paths, make sound architectural calls, and take a project to completion with minimal guidance.
- Thrives in a Startup Environment: You are energized by a fast-paced, evolving startup environment, are comfortable when requirements pivot, and are explicitly not looking for a predictable, mature role at a big company.
- Wears Multiple Hats Comfortably: You gladly step outside a narrow engineering lane. You can context-switch seamlessly between core backend engineering, customer fire drills, and partner-facing implementation without losing quality.
- Customer-Facing Technical Experience: Proven ability to interface with product teams, solution architects, and customer stakeholders to translate vague user requirements into working, deployed software.
- Strong Documentation Culture: A consistent habit of writing clear system designs and deployment guides so that the next team member never has to start from zero.
Nice to haves
- Familiarity with durable execution systems or workflow engines (e.g., Temporal, Airflow, Camunda).
- Experience designing plugin, connector, or developer framework ecosystems.
- Understanding of Edge/serverless computing or Backend-for-Frontend (BFF) patterns for customer-facing apps.
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