Associate Director, AI & Applied Solutions
USFull-TimeDirector
Salary140,000 - 190,000 USD per year
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Job Details
- Experience
- 6–10 years
- Required Skills
- AWSPythonArtificial IntelligenceGCPSnowflakeTypeScriptAzureData engineeringData scienceCommunication SkillsCI/CDDevOpsDatabricksPrompt EngineeringMLOpsGenerative AI
Requirements
- 6–10 years of relevant experience in consulting, corporate strategy, investment banking, private equity, or analytics-focused roles.
- Proven hands-on experience building or supporting GenAI applications, LLM-based systems, or AI/ML prototypes in real-world environments.
- Strong technical fluency in LLM APIs, prompt engineering, RAG, agent frameworks, and AI evaluation techniques.
- Proficiency in Python and/or TypeScript, with experience using AI-assisted coding tools.
- Understanding of data engineering and DevOps/MLOps practices including CI/CD, ETL/ELT, orchestration tools, and cloud platforms.
- Familiarity with modern AI and data platforms such as Snowflake, Databricks, AWS, Azure, or GCP.
- Strong consulting and communication skills with the ability to engage executive-level stakeholders and present technical concepts clearly.
- Bachelor’s degree required; advanced degree in a quantitative or technical field preferred.
Responsibilities
- Lead client engagements by designing and delivering AI- and data-driven solutions that address operational, strategic, and financial challenges.
- Build and prototype GenAI applications, including agents, copilots, RAG systems, and analytics tools using modern AI frameworks and development environments.
- Apply structured problem-solving and hypothesis-driven consulting methods enhanced by AI and data science capabilities.
- Translate complex AI outputs into actionable business insights, executive-ready recommendations, and measurable impact assessments.
- Shape the internal AI technology stack, including frameworks, orchestration tools, data platforms, and DevOps/MLOps practices.
- Develop reusable IP such as accelerators, agent templates, prompt libraries, and reference architectures.
- Mentor and evangelize AI adoption across teams, supporting both technical skill development and consulting excellence.
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