Associate Director, AI & Applied Solutions

Associate Director, AI & Applied Solutions

At SSA & Company, our values, relationships, and people drive everything we do. We work in a flat structure that values every individual’s input, and deploy agile, light‑footprint teams of typically 3–5 consultants.

• Partner with engagement leaders to design and deliver advanced quantitative and qualitative analyses across operational, strategic, and economic dimensions—now augmented by AI and data science.
• Serve as the day‑to‑day face of the firm and primary point of contact, leading teams and building deep relationships with clients across industries.
• Apply SSA’s hypothesis‑driven problem solving and structured disaggregation to solve complex client challenges.

• Build working prototypes for clients—apps, agents, copilots, RAG systems, and analytical tools—using modern (Gen)
  AI dev tools (e.g., Claude Code, Cursor, Lang Chain/Lang Graph, vector stores, agent frameworks).
• Apply lightweight data engineering and Dev Ops practices (clean pipelines, version control, CI/CD, evaluation, monitoring) so prototypes are demoable, repeatable, and credible to client engineering teams.
• Execute applied data science: hypothesis generation, model selection, evaluation, and deployment of ML/LLM‑based solutions tied to clear business outcomes.
• Synthesize analysis and AI outputs into high‑value insights, actionable recommendations, and financial impact projections (hard and soft benefits).

• Shape SSA’s tech stack across the AI delivery lifecycle—models, frameworks, data platforms, orchestration, and Dev Ops/MLOps tooling—with opinionated, evidence‑backed recommendations.
• Pioneer new techniques in AI/LLMs: agentic systems, multi‑agent orchestration, RAG, fine‑tuning, and evaluation frameworks.
• Champion the data engineering and Dev Ops foundations that make AI work in production—reliable pipelines, well‑modeled data, environments, CI/CD, and observability.
• Build internal IP—accelerators, reference architectures, prompt libraries, agent templates, and analytical frameworks.

• Above all, deliver measurable client value—revenue growth, cost optimization, risk management, customer/employee experience—using AI, data, and data science as levers.
• Establish KPIs to track AI‑enabled transformation and translate technical concepts into compelling narratives for executive and board‑level audiences.

• Mentor colleagues firmwide on using AI tools—coding assistants, agents, prompt craft—and develop juniors in both technical and consulting craft.
• Evangelize AI in consulting internally and externally; produce high‑quality PowerPoint and live demos for line‑manager‑to‑board audiences.

• 6–10 years of progressive experience; prior consulting (top management consulting), corporate strategy, or investment banking/PE strongly preferred.
• Demonstrated experience supporting or leading AI, data, and analytics initiatives—ideally including hands‑on building of Gen AI applications, agents, or LLM‑powered prototypes shipped to real users.
• Exposure to financial services (P&C, life, banking, wealth) and/or retail, healthcare, or manufacturing is a plus.

• Hands‑on fluency with (Gen)
  AI dev patterns: LLM APIs, prompt engineering, RAG, agentic frameworks, evaluation, and tool/function calling.
• Comfort shipping code with AI coding assistants (Claude Code, Cursor, Copilot); able to read, write, and review Python and/or Type Script.
• Working knowledge of data engineering (ETL/ELT, data modeling, orchestration with Airflow/dbt/Dagster, streaming/batch, feature/vector stores) and Dev Ops/MLOps fundamentals (Git, CI/CD, Docker, IaC, monitoring, AI evaluation/observability).
• Familiarity with cloud data and AI platforms (Snowflake, Databricks, Big Query, AWS/Azure/GCP AI services) and core ML concepts.

• Superb written and oral communication; able to present to senior executives and credibly demo working software.
• Resilience, critical thinking, and comfort in ambiguous, fast‑paced environments with executive…