Director, AI Engineer

dentsu Austria

. Lead dentsu's applied AI engineering team for the Data Experience practice .

Posted 10/13/2026full-timeUnited StatesLead💰 $94,000 - $170,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in leading AI engineering teams and building full-stack web applications with a focus on agentic systems and context engineering. Proficient in deploying models on Databricks and implementing AI-native development standards.

Highest-signal resume keywords

AI Engineering LeadershipFull-Stack Web Application DevelopmentContext EngineeringDatabricks Model DeploymentClaude Agent SDK Experience

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Hard Skills

PythonLangGraphFastAPIREST APIsJavaScriptToken ManagementOptimization StrategiesAgentic Harness EngineeringCI/CDModel Evaluation

Soft Skills

Team LeadershipCross-Time Zone CollaborationProblem SolvingCommunication

Tools & Technologies

DatabricksMLflowClaude CodeCursorCodexGitHub ActionsSparkPySpark

Industry Keywords

MediaAdvertising TechnologyMarketing AnalyticsLakehouse ArchitectureGoverned Gold Data Products

Tech Stack

Tools & technologies

JavaScriptNext.jsPostgresPySparkPythonReactSparkSQLUnity

About the role

Key responsibilities & impact

Lead dentsu's applied AI engineering team for the Data Experience practice
Own the full stack of shipped products, including web applications, agentic harnesses, and model hosting and observability on Databricks
Lead and develop a senior India-based AI engineering team across time zones
Build full-stack web applications with Python services, APIs, and modern front ends
Engineer the agentic harness for tool calling, state, memory, retries, guardrails, human-in-the-loop checkpoints, and evaluation
Design multi-agent systems in LangGraph, including supervisor structures, sub-agent routing, A2A communication, and shared state
Ship embedded assistants, tool-using workflows, and streaming user experiences inside web apps
Own context engineering, including retrieval, summarization, compaction, tool-result shaping, and memory strategy
Drive token management and optimization, prompt caching, model routing, context budgets, and cost and latency tracking
Host and operate models and agents on Databricks using Model Serving, Unity Catalog, and MLflow 3
Set AI-native development standards using Claude Code, Cursor, and Codex
Run GitHub engineering hygiene, including branching, code review, CI/CD, automated testing, and environment promotion
Partner with product, data engineering, and client teams to translate business problems into agent designs and explain trade-offs

Requirements

What you’ll need

8+ years in software engineering
2+ years building LLM-powered or agentic systems in production
Experience leading senior engineers
Strong hands-on experience with the Claude Agent SDK or OpenAI Agents SDK (or equivalent)
Experience engineering agentic harnesses, including tool orchestration, state management, error recovery, guardrails, and evaluation
Deep context engineering skills, including token management, optimization, and prompt caching strategies
Expert Python and strong LangGraph experience, including supervisor and multi-agent patterns and agent-to-agent communication
Experience building full-stack web applications with Python backends, FastAPI or similar, REST and streaming APIs, and modern JavaScript front ends such as React or Next.js
Experience deploying models and agents on Databricks with MLflow, including MLflow 3 tracing and evaluation
Fluency with Claude Code, Cursor, or Codex
Solid DevOps fundamentals on GitHub, including CI/CD pipelines, GitHub Actions, code review, testing, and secrets and environment management
Track record managing distributed or offshore engineering teams across time zones
Preferred: Spark/PySpark, lakehouse architecture, SQL, governed gold data products
Preferred: Model Context Protocol (MCP) servers or A2A protocol
Preferred: LLM evaluation practice, including offline eval sets, LLM-as-judge, and regression testing
Preferred: Databricks Apps and Lakebase (Postgres)
Preferred: experience in media, advertising technology, or marketing analytics environments

Benefits

Comp & perks

Medical, vision, and dental insurance
Life insurance
Short-term and long-term disability insurance
401k
Flexible paid time off
At least 15 paid holidays per year
Paid sick and safe leave
Paid parental leave
In-person collaboration and flexible working arrangements depending on location and business needs