Senior, AI Engineer

WHAT MAKES US A GREAT PLACE TO WORK
We are proud to be consistently recognized as one of the world's best places to work. We are currently the top ranked consulting firm on Glassdoor’s Best Places to Work list and have earned the #1 overall spot a record seven times. Extraordinary teams are at the heart of our business strategy, but these don't happen by chance. They require intentional focus on bringing together a broad set of backgrounds, cultures, experiences, perspectives, and skills in a supportive and inclusive work environment. We hire people with exceptional talent and create an environment in which every individual can thrive professionally and personally.

WHO YOU'LL WORK WITH

You'll join our engineering experts within the AI, Insights & Solutions (AIS) team . This team is part of Bain's digital capabilities practice, which includes experts in analytics, engineering, product management, and design. In this multidisciplinary environment, you'll leverage deep technical expertise and business acumen to help clients tackle their most transformative challenges. You'll work on integrated teams alongside our general consultants and clients to develop data-driven strategies and innovative solutions. Together, we create human-centric solutions that harness the power of data and artificial intelligence to drive competitive advantage. Our collaborative and supportive environment fosters creativity and continuous learning, enabling us to consistently deliver exceptional results.

WHERE YOU'LL FIT WITHIN THE TEAM

The Senior AI Engineer will build and ship generative AI systems and agentic solutions for Bain's clients. You will contribute across the development lifecycle -- from prototyping through to production deployment -- working closely with engineers, product managers, and data scientists. This is a hands-on individual contributor role focused on delivering high-quality technical output and deepening your expertise across the AI Engineering skillset.

WHAT YOU'LL DO

• Build and deploy end-to-end generative AI systems, including agentic workflows and production-grade AI applications
• Build and iterate on multi-component AI pipelines, including:
• Retrieval-Augmented Generation (RAG)
• Fine-tuning and parameter-efficient tuning
• Embedding generation and optimization
• Hybrid retrieval strategies (vector, graph, keyword)
• Implement tool use, function calling, and orchestration across AI workflows
• Build agentic systems with sound engineering principles around separation of concerns, memory architecture, and tool integration
• Contribute across the full stack: model experimentation, evaluation design, and production system deployment
• Build and maintain APIs, microservices, CI/CD pipelines, and cloud-native deployments with attention to observability and reliability
• Support GenAIOps processes including automated testing, regression evaluation, and latency monitoring
• Apply performance, safety, and responsible AI principles across system design, including guardrails, fallbacks, and human-in-the-loop (HITL) workflows
• Build evaluation frameworks covering hallucination rate, factual consistency, relevance, latency, throughput, and cost
• Collaborate effectively with product, engineering, data science, and infrastructure teams
• Communicate technical findings clearly to cross-functional stakeholders

MUST HAVE

• 2-4+ years in software engineering, ML engineering, or applied AI roles with hands-on building responsibilities
• Demonstrated experience shipping generative AI features or systems end-to-end, from prototyping through production
• Solid prompt engineering and context engineering skills
• Working knowledge of evaluation design and data labeling strategies for LLM applications
• Experience with
• RAG architectures (vector-based retrieval; exposure to hybrid or graph-based approaches is a plus)
• Agentic patterns (tool use, routing, memory management)
• AI-Specific Tools & Frameworks - Orchestration frameworks, Vector and graph databases and Model + API ecosystems
• Strong foundation in software engineering, system design, and production-grade deployment
• Familiarity with cost and latency tradeoffs when working with LLM workloads
• Clear communication skills with the ability to explain technical concepts to non-technical collaborators
• Comfort operating in high-ambiguity, collaborative environments
• Experience in client-facing consulting or enterprise transformation environments is a strong plus

WORKING MODEL & TRAVEL

• This role requires a minimum of 3 days per week working together in person, either at a client location or at your Bain home office.
• Travel is required beyond your home office / primary working location. Frequency and destination vary by project needs.