AI Engineer — Production-Ready ML & Agentic Systems

Bain Capital

Boston (MA)

On-site

USD 140,000 - 230,000

Full time

3 days ago
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Job summary

Bain Capital is seeking an AI Engineer to join the Data Science & AI team in Boston. You will develop and deploy AI solutions across the firm, collaborating with Investment teams to enhance decision-making and streamline processes.

You will implement production‑ready AI systems, champion best practices, and shape the roadmap for AI products. The role requires strong Python expertise, experience with agentic AI, and a track record of delivering scalable AI solutions in production, along with a

Qualifications

  • BS or MS in CS, DS, ML, or related field.
  • Several years of production ML/NLP experience.
  • Ability to own projects end-to-end.
  • Strong communication with technical and non-technical stakeholders.
  • Self-starter with adaptability in a fast-paced environment.

Responsibilities

  • Design, build, fine‑tune, and deploy AI models and agentic applications.
  • Collaborate with business users to gather requirements and deliver insights.
  • Evaluate performance: accuracy, latency, scalability, and cost.
  • Build robust data pipelines with labeled datasets for training/inference.
  • R&D and thought leadership; stay updated on AI methods and tools.
  • Mentor junior engineers and lead internal AI best-practices sessions.

Skills

AI engineering
Agentic AI
RAG workflows
Cloud & DevOps
Data engineering
Stakeholder comms
Leadership

Education

BS or MS in CS/DS/ML

Tools

Pinecone
Docker
Kubernetes
Terraform
MLflow

Job description

Bain Capital is seeking an AI Engineer to join the Data Science & AI team in Boston. You will develop and deploy AI solutions across the firm, collaborating with Investment teams to enhance decision-making and streamline processes.

You will implement production‑ready AI systems, champion best practices, and shape the roadmap for AI products. The role requires strong Python expertise, experience with agentic AI, and a track record of delivering scalable AI solutions in production, along with a

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