Head of AI Engineering – Architecture, Agents

GoOpti - Dynamic Shuttle

. Architect the agent platform, including orchestration, internal-system/data access, context and memory, monitoring, and human-in-the-loop controls .

Posted 11/7/2026full-timeLjubljana • United StatesLead💰 €75,000 - €100,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in architecting AI systems, including backend engineering with Java, REST API design, and data modeling with SQL. Proven ability to lead teams, manage agent orchestration, and implement self-improving systems while ensuring compliance with security and GDPR standards.

Highest-signal resume keywords

Backend Engineering SkillsLLM-Based Systems ExperienceREST API DesignData Modeling with SQLAgent Orchestration

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

JavaPythonTypeScriptSQLMySQLPostgreSQLLLM SystemsData SystemsREST APIsContext Management

Soft Skills

CollaborationCommunicationProblem-SolvingLeadership

Tools & Technologies

MCP ServersObservability ToolingOpenAIAnthropic

Industry Keywords

GDPRAutonomous AgentsMulti-Agent OrchestrationOperational DataBusiness Rules

Tech Stack

Tools & technologies

JavaMySQLPostgresPythonSQLTypeScript

About the role

Key responsibilities & impact

Architect the agent platform, including orchestration, internal-system/data access, context and memory, monitoring, and human-in-the-loop controls
Build and ship AI systems connecting to the Java backend, APIs, and databases
Create a machine-readable company knowledge layer combining operational data, business rules, and working knowledge
Build the tool/MCP layer over booking, pricing, planning, analytics, and finance systems
Implement agent orchestration, hand-offs, memory, context management, observability, tracing, evaluations, permissioning, and approval checkpoints
Launch autonomous agents for marketing, development, finance, customer care, pricing/planning, and sales
Develop self-improving loops where supervisor agents diagnose failures, propose fixes or policy changes, test them, and open merge requests for approval
Own model selection, token budgets, evaluations, and cost-per-booking reporting
Run weekly intake and prioritization of departmental problems with owners, measures, and go/no-go gates
Lead one or two contract AI developers, collaborate with the backend team, and teach managers to write effective agent specifications
Deliver the stated platform, agent-skill, knowledge-capture, and improvement-loop milestones through September 2027

Requirements

What you’ll need

6+ years building backend or data systems, including 2+ years shipping LLM-based systems in production
Experience with tool use, retrieval, evaluations, and agents
Experience handling context limits, tool-calling failures, runaway costs, and silent regressions
Strong backend engineering skills in a large Java codebase
Ability to design clean REST APIs and integrate with existing services
Python or TypeScript for AI tooling
Solid data modelling and serious SQL skills with MySQL/PostgreSQL
Ability to design for scale, security, and GDPR
Record of building practical systems quickly in a small company with existing systems
Ability to explain trade-offs to non-technical managers and know when to say no
Fluent English
Nice to have: MCP servers and multi-agent orchestration in production
Nice to have: LLM observability/evaluation tooling and model routing across OpenAI, Anthropic, and open models
Nice to have: Travel, mobility, marketplace, routing, or operations research experience

Benefits

Comp & perks

Bonus and equity (TBC)
Budget for models, tools and evaluations
25+ days of vacation
Team buildings and in-person meetups
Direct access to company leadership
Open mandate to shape the AI architecture of the whole company