Senior Agentic Engineer

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🕒 vor 3 Tagen

🇺🇸 Vereinigte Staaten – Remote

⏰ Vollzeit

🟠 Senior

👷🏻‍♀️ Ingenieur

👻 Geisterscore 25%

Was es bedeutet: die Wahrscheinlichkeit, dass für diese Stelle niemand wirklich einstellt.So liest du es: 60 % oder höher heißt, wir halten das für einen Geisterjob. Niedrigere Werte sind weniger bedenklich.Warum dieser Wert:

• Seit 3 Tagen offen.
• Stellen bei diesem Unternehmen werden meist in 153 Tagen besetzt.
• Kein Gehalt angegeben.

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Brahma

WebsiteLinkedInAlle Stellen

11 - 50 Mitarbeiter

Gegründet 2022

₿ Crypto

💳 Fintech

🔌 API

💰 €4.206.900 Seed Round - Brahma im 2022-02

Crypto • Fintech • API

Brahma ist eine entwicklerorientierte Orchestrierungsschicht, die die Onchain-Finanzlogik mit Offchain-Zahlungs- und Abwicklungssystemen verbindet. Sie ermöglicht programmierbare Kapitalflüsse über Blockchains, Strategien und traditionelle Zahlungswege und bietet Smart Accounts, automatisierte Agenten und programmierbare Kartenausgabe, damit Anwendungen Onchain-Positionen in reale Ausgaben umwandeln können. Brahma abstrahiert Infrastruktur und Abwicklung für Entwickler, sodass sie Onchain- oder hybride Anwendungen aufbauen können, ohne Backend-Operationen durchführen zu müssen.

Beschreibung

• Build, ship, and operate components of Brahma’s internal agentic setup • Build gateway and routing features including provider fallbacks, budget enforcement, usage attribution, and access policies • Build and operate MCP servers and connectors to Git, CI/CD, work tracking, and documentation • Own CI/CD, containers, and infrastructure-as-code for agentic AI services • Implement governed agent workflows with structured inputs and outputs, human approval gates, and multi-agent patterns • Build and operate memory and context services including session and long-term memory, context compaction, retrieval, and progressive tool disclosure • Own production operations including monitoring, alerting, rollbacks, cost management, incident response, upgrades, and patches • Write unit tests, integration tests, and regression evaluations for agents, tools, and routing in CI • Own tracing and usage-reporting pipelines across model, tool, and agent calls • Build components according to security standards and fix security findings • Maintain services and open-source dependencies, diagnose failures to root cause, and participate in incident response and future on-call rotation • Build and maintain developer surfaces including CLI, chat integrations, coding-agent harness configuration, and shared agent and skills catalogs • Help teams adopt coding agents through documentation, examples, and pairing • Document solutions and share patterns and lessons through demos, guides, and pairing • Contribute to design reviews and architecture decision records, vet emerging agent frameworks, and harden effective patterns for enterprise scale

🎯 Anforderungen

• 5+ years of software engineering experience • Primary expertise in server-side Python development • Hands-on experience shipping production features built on LLM APIs and tool calling, including failure modes and cost considerations • Experience building MCP servers or equivalent tool connectors, not only consuming them • Proven experience building reliable APIs, services, and asynchronous or event-driven systems • Experience with automated testing, CI, logging, metrics, tracing, and debugging production issues • Practical knowledge of OAuth 2.0, OIDC, secrets management, least privilege, and LLM-specific risks such as prompt injection • Track record of documenting work and helping colleagues and teams adopt new technology • Pragmatic daily use of AI coding tools such as Claude Code, Cursor, or Copilot while maintaining code quality, test coverage, and review standards • Experience with A2A, agent frameworks such as LangGraph or Google ADK, or durable workflow engines such as Temporal or Prefect • Experience with agent memory designs, vector databases such as pgvector or Qdrant, or hybrid search • Experience configuring coding agents for teams, including skills, subagents, hooks, and sandboxing • Experience running a multi-model gateway or routing layer in production is nice to have • Experience with LLM evaluation tools, LLM-judged regression tests, and OpenTelemetry is nice to have • Track record of bringing emerging agent tools or patterns from evaluation into production is nice to have • Experience running services on GCP, AWS, or Azure with Docker, Kubernetes, and Terraform or equivalent infrastructure-as-code is nice to have

🏖️ Vorteile

• Remote work arrangement with working hours overlapping UTC+0 to UTC+3 • Opportunity to work with cutting-edge generative AI models and enterprise media technology • Dedicated, high-caliber agentic AI unit • Collaboration with Architect, Product Management, ML Engineering, Security Engineering, and Infrastructure & DevOps teams • Exposure to open protocols, open-source components, and proprietary services • Opportunity to build and ship production agentic AI systems • Knowledge sharing through demos, guides, documentation, and pairing

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