Lead Backend Engineer – Automation

Job Title: Lead Backend Engineer – Automation 

About Assembly Industries

Talent is distributed but Opportunities are not - Assembly Industries is breaking that pattern by building an AI enabled talent platform that connects top-tier, highly skilled global professionals with innovative companies across the US. As a fast-growing startup, we are laser-focused on impactful growth, agile strategies, and exceptional results.

Role Overview

As a Lead Engineer focused on Backend Automation Infrastructure, you will be a foundational contributor to our internal orchestration platform—a mission-critical system that powers the intelligent automation layer across Assembly’s products and services.

This isn’t just a “tools and scripts” automation role. You will help architect, design, and implement a robust orchestration engine, built using Java microservices and a NoSQL document database, that underpins our AI-enabled operations. While you’re expected to have familiarity with AI/LLM-based workflows and emerging automation patterns (RAG, agents, chaining), your core responsibility is building backend systems that are reliable, scalable, and extensible for automation.

You will also collaborate with Engineering, Product, and Solution Enablement teams to expose automation capabilities as APIs and internal services, while ensuring the orchestration layer integrates seamlessly with other systems and LLM-based agents.

Key Responsibilities

🧱 Backend Systems Architecture & Development

• Design and build the backend orchestration platform that powers automation workflows at Assembly.
• Lead the development of Java-based microservices and distributed components responsible for task execution, state management, and orchestration logic.
• Model and manage NoSQL document databases for tracking task states, contexts, metadata, and agent workflows.
• Define internal API contracts, services, and system boundaries that enable modular orchestration logic and integration with LLMs or external APIs.

🧠 LLM-Aware System Design

• Collaborate on infrastructure that supports agentic workflows, RAG pipelines, and other AI-native use cases.
• Architect services that support:
  • Document chunking and metadata extraction
  • Embedding indexing with vector databases
  • Prompt chaining and context injection
     
• Work with AI and Product teams to design systems that are extensible to evolving LLM tooling and chaining methods (e.g., Chain of Thought, ReACT, Tree of Thought).

🤖 Automation Platform Enablement

• Integrate third-party APIs and automation layers (e.g., n8n, Make, Workato, or internal tools) into the orchestration fabric as plugins or services.
• Provide extensible APIs and libraries for building reusable automation blocks or launching agents programmatically.
• Collaborate with frontend and systems engineers to surface automation configuration, execution results, and observability.

🧪 Prototyping & Support for Emerging AI Use Cases

• Work with solution engineers and AI specialists to prototype LLM-integrated automation flows.
• Build internal tooling for LLM evaluation, tracing, prompt versioning, and response debugging.

Key Skills & Qualifications

Core Backend Engineering

• 6+ years of software engineering experience, including system design and distributed architecture.
• Strong proficiency in Java, especially for building scalable microservices.
• Experience with NoSQL document databases (e.g., MongoDB, Firestore, Couchbase).
• Deep understanding of distributed systems patterns—queues, retries, idempotency, service orchestration.
   

Automation & AI-Aware System Experience

• Familiarity with automation platforms (Zapier, Make, n8n, or in-house tools).
• Strong working knowledge of Python scripting and API-based integrations.
• Understanding of LLM architectures, embedding systems, vector search (e.g., FAISS, Pinecone), and prompt engineering techniques.
• Experience or interest in agent frameworks like LangChain, CrewAI, or similar.
• Awareness of prompt chaining strategies and memory/context persistence across sessions.
   

Cross-Functional Collaboration

• Comfort working with solution architects, AI engineers, and product stakeholders to translate business problems into backend architecture.
• Strong communication skills and ability to document systems for a cross-disciplinary team.

Nice to Have

• Experience with distributed task orchestration systems (e.g., Temporal, Airflow, Camunda).
• Background in building workflow engines, plugin frameworks, or agent spawning/execution systems.
• Contributions to open-source orchestration, LLM tooling, or automation platforms.
   

Bonus Points

If this is a new field for you, but you’ve built RAG, agentic, or automation backend projects on your own and can showcase them, that would be a huge plus. We highly value demonstrated capability over prior job titles.

This is a remote opportunity open to all candidates based in Argentina. 

*Your application includes a quick AI interview