Associate Director, AI & Applied Solutions

New

JobgetherAI consulting

Based in the United StatesFull-TimeDirector

SalaryAnnual starting base salary ranging from $140,000 to $190,000

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Job Details

Experience: 6–10 years of progressive professional experience.
Required Skills: PythonMachine LearningTypeScriptData engineeringCI/CDPrompt EngineeringGenerative AI

6–10 years of progressive professional experience.
Experience supporting or leading AI, data, and analytics initiatives.
Practical knowledge of generative AI development patterns, including LLM APIs, prompt engineering, RAG, agentic frameworks, tool/function calling, and model evaluation.
Ability to develop, read, and review code in Python and/or TypeScript.
Experience with AI-powered coding assistants such as Claude Code, Cursor, or GitHub Copilot.
Working knowledge of data engineering concepts, including ETL/ELT pipelines, data modeling, orchestration, batch and streaming architectures, and feature or vector stores.
Familiarity with Airflow, dbt, or Dagster, and DevOps/MLOps fundamentals including Git, CI/CD, Docker, infrastructure as code, monitoring, evaluation, and observability.
Familiarity with Snowflake, Databricks, BigQuery, and AI services across AWS, Azure, or Google Cloud.
Strong understanding of core machine learning concepts and their business applications.
Bachelor's degree with strong academic credentials; a relevant master's degree is strongly preferred.
Willingness and ability to travel multiple days per week, including occasional international assignments.
Top-tier management consulting, corporate strategy, investment banking, or private equity experience is strongly preferred.

Partner with engagement leaders to design and deliver quantitative and qualitative analyses using AI and data science.
Serve as a primary client contact, lead project teams, and build stakeholder relationships.
Design, build, and demonstrate AI applications, agents, copilots, RAG systems, and analytical tools.
Apply data engineering and DevOps practices, including reliable pipelines, version control, CI/CD, evaluation, and monitoring.
Execute applied data science initiatives, including hypothesis development, model selection, evaluation, and deployment.
Shape the AI technology stack and implement emerging techniques such as agentic systems, multi-agent orchestration, RAG, and fine-tuning.
Develop reusable technical assets, reference architectures, prompt libraries, agent templates, and analytical frameworks.
Establish KPIs and deliver measurable business outcomes through AI-enabled initiatives.
Mentor colleagues and create presentations and demonstrations for business and executive audiences.

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