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

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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