Senior Agentic Platform Engineer

IT (programavimas)

Remote, Lithuania

€6000 - €7500 bruto

Pagrindinis Kandidatams Senior Agentic Platform Engineer

Apie kompaniją

VaultSpeed builds software that speeds up data warehouse delivery. Its Data Vault platform automates data warehouse code generation, and its newer agentic AI platform lets data teams work with the platform through AI.

Darbo aprašymas:

About the role

You’ll join VaultSpeed’s small Agentic team as a hands-on senior engineer, building AI agents that customers rely on in production. The platform runs on Omnigent, an open-source agent platform that VaultSpeed extends for enterprise use, with a graph-based context store and Data Vault expertise packaged into the agents as skills.

The work spans the whole stack: the agents and their skills, the platform services they run on, the Kubernetes infrastructure behind them and the interface people use. You’ll own areas of the system from technical design to release, and your decisions will shape how a new product grows.

What you’ll do

Build and improve the agents that ingest sources and generate data models and code, and the skills that carry data modelling knowledge, deciding what belongs in a prompt, a skill, a tool or plain deterministic code
Build evaluations and regression suites, so changes to prompts, models and tools are judged on evidence
Extend the platform layer on top of Omnigent: multi-tenancy and tenant isolation, authentication, the MCP tool suite, the context store, the agent marketplace and the LLM gateway
Keep the Omnigent fork in sync with upstream, resolve conflicts with customisations and contribute fixes back to the open-source project
Work on the Kubernetes sandbox infrastructure where agents run (templates, warm pools, persistence, suspend and resume, observability, cost) and ship changes through GitOps with Argo CD
Investigate agent failures through logs and model traces, and fix root causes rather than symptoms
Write technical proposals, review designs and pull requests, and support releases

Reikalavimai:

Requirements:

5+ years of professional software engineering, including owning the technical design of significant components through to production
Hands-on experience shipping LLM-based features to real users (beyond prototypes): tool calling, structured outputs, context management
Strong back-end fundamentals: services and APIs, authentication, data modelling, databases
Docker and hands-on experience deploying and debugging services on Kubernetes through a GitOps workflow
Comfortable working in a large codebase you don’t own and resolving non-trivial merge conflicts
Strong analytical thinking: you get from a vague symptom to a root cause, also in non-deterministic systems
Daily use of AI coding tools such as Claude Code or Cursor
Experience working in a Scrum team across a distributed setup
Fluent English

Nice to have

MCP, the Claude Agent SDK, LangGraph or similar agent frameworks
LLM evaluation and observability tools such as MLflow or Langfuse
Graph databases (Neo4j)
Multi-tenant SaaS and identity: OIDC, SSO, WorkOS or similar
Kubernetes agent-sandbox or other sandboxed execution environments
Data engineering or data warehousing
Maintaining a fork of, or contributing to, an active open-source project
Comfortable making minor front-end changes

Kompanija siūlo:

Building an AI product in a well-defined domain, where agent output can be checked against a real model
Joining a new product early, in a small team where your design decisions shape the platform
Remote work in a team organised around trust and outcomes
Private health insurance
Company events