16 publicaciones de empleo destacadas de principal engineer, context & knowledge systems en buenos aires, b (¡Están contratando!)

Agentic Process Implementer / Architect
Band of Coders —Buenos Aires, Buenos Aires
Postulación rápida
5d
Senior Data Engineer – Data Operations
MetLife —Capital Federal, Buenos Aires
- Tiempo completo
AI Engineers + Platform Architect - EY GDS
EY —Capital Federal, Buenos Aires
4d
Data Engineer Ssr/Sr
Lovelytics —Buenos Aires, Buenos Aires
Senior Business Analyst
EY —Capital Federal, Buenos Aires
Ingeniero civil especialista en IA
Stantec —Buenos Aires, Buenos Aires
Performance Marketing Lead (Social Media Ads)
Ruby Labs —Buenos Aires, Buenos Aires
- Tiempo completo
Senior Software Engineer | Data Platform
Humand —Buenos Aires, Buenos Aires
Senior Salesforce Developer
Launchpad Technologies —Capital Federal, Buenos Aires
Postulación rápida
Pre Sales Engineer - HPE Networking
TD Synnex —Capital Federal, Buenos Aires
- Tiempo completo
13d
Lead C# Software Architect
Marvik —Buenos Aires, Buenos Aires
Ingeniero Civil Geotécnico
Stantec —Buenos Aires, Buenos Aires
Technical Leader – Python / .NET / Azure / IA
Talent Connect —Capital Federal, Buenos Aires
15h
Ingeniería de Reservorios
Schlumberger —Buenos Aires, Buenos Aires
Ing. de Datos e Infraestructura
Schlumberger —Buenos Aires, Buenos Aires
Mobile Engineer (Remote)
Fireblocks —Buenos Aires, Buenos Aires
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Agentic Process Implementer / Architect

Band of Coders
Buenos Aires, Buenos Aires

Postulación rápida

Detalles del empleo

Hace 5 días

Descripción completa del empleo

About the Role

At Band of Coders, we are pushing the boundaries of automation and intelligence. We are looking for an Agentic Process Implementer / Architect to design, build, and optimize the next generation of intelligent workflows and processes for our clients.

You will lead the transition toward autonomous AI agents and automated cross-checking systems, ensuring infrastructure is robust, scalable, and highly monitored. This is a high-impact role, where you will orchestrate the integration of AI processors with major cloud infrastructures.

Key Responsibilities

1. Workflow Architecture & Automation

Design, implement, and maintain advanced agentic processes and automated workflows.
Develop and enforce mandatory monitoring workflows that require systematic data cross-checks.
Standardize internal review processes, making the cross-checking of historical data and past notes a mandatory, seamless habit for all teams.

2. Cloud & AI Infrastructure Integration

Lead the integration of AI processors and cloud infrastructure.
Architect and manage secure, scalable environments across AWS, Google Cloud Platform (GCP) and Azure.
Ensure CI/CD pipelines are fully optimized for deploying AI-driven process models.

3. Collaboration & Continuous Improvement

Partner with engineering leadership to align technical workflows with operational needs.
Act as the bridge between raw AI processor capabilities and practical, day-to-day team workflows.

Requirements & Qualifications

State-of-the-Art LLMs & Frontier Models: Experience optimizing and routing across multi-provider environments including OpenAI (GPT-4o/o1/o3), Anthropic (Claude 3.5 Sonnet/Opus), and open-weight models (Llama 3/3.1/3.2, Mistral).
Agentic Frameworks & Ecosystems: Proven track record with graph-based or role-based orchestration systems such as LangGraph, CrewAI, PydanticAI (for type safety), Hugging Face smolagents, or cloud-native toolkits (Google ADK, OpenAI Agents SDK).
Model Context Protocol (MCP): Hands-on experience implementing or building custom MCP servers (e.g., GitHub, Playwright for browser automation, PostgreSQL/Supabase, Filesystem, or Enterprise API connectors) to cleanly decouple model reasoning from tool execution.
Structured Outputs & Function Calling: Deep understanding of JSON schema enforcement, tool definition, and prompt optimization via tools like DSPy or Instructor to guarantee deterministic system inputs/outputs.
Vector DBs & RAG Tools: Integration of agent memory and knowledge retrieval using Pinecone, Milvus, or pgvector, optimized for long-term state retention.
Cloud Expertise: Hands-on experience architectural design and deployment in AWS, Google Cloud Platform (GCP) and/or Azure.
Monitoring & Data Integrity: Strong background setting up robust monitoring tools, data validation systems, and mandatory cross-checking pipelines.
Problem-Solving Mindset: Ability to take loose operational needs and turn them into strict, bulletproof technical guardrails.
Immediate Impact: Ready to hit the ground running.

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About the Role

Key Responsibilities

1. Workflow Architecture & Automation

2. Cloud & AI Infrastructure Integration

3. Collaboration & Continuous Improvement

Requirements & Qualifications

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