Providing strategic and technology advisory leadership across AI strategy, transformation and transaction engagements.
Responsibilities
Advising clients on AI target architectures and evaluating architectural options against business objectives, value creation opportunities, investment constraints and risk considerations
Structure ambiguous client problems into hypotheses, analyses and actionable recommendations
Designing end-to-end AI target architectures spanning data foundations, models, orchestration, integration, security, enterprise systems and the operating model required to run them
Assessing AI, technology and data maturity of enterprises including the credibility of data/AI claims, the durability of application landscape, infrastructure and data to scale AI in a enterprise context and translating findings into executive recommendations, investment priorities and transformation roadmaps
Defining AI solutions for targeted use cases or complex AI products that span across value streams that are underpinned by existing enterprise IT & data landscapes, including prioritisation of use cases based on value, feasibility, scalability and strategic relevance
Requirements
Masters degree or equivalent in Computer Science, Engineering, Mathematics, Data Science or related analytical discipline from a reputable university
Nice to have: Technology, digital or AI diligence engagements
Experienced Machine Learning Engineer to join the AI and machine learning team, delivering machine learning models and applications across trading, operations, and support functions, with a focus on GenAI projects.
Responsibilities
Design, develop, and deploy end-to-end machine learning and data science solutions across business activities
Drive adoption and development of the firm's internal GenAI platform and applications
Design, prototype, and deploy agentic LLM workflows, including tool use and function calling
Evaluate and benchmark LLM and agentic solutions
Apply a broad range of modelling techniques (time-series forecasting, NLP, classification, generative AI) to commodity pricing and operational optimisation problems
Requirements
Master’s degree or equivalent in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field
Act as the trusted technical advisor for customers across their adoption of AWS
Lead technical deep-dives, architecture reviews, workshops and proof-of-concept engagements
Design AI/ML and generative-AI architectures
Apply and promote AIDLC practices
Help customers build evaluation frameworks
Requirements
Nice to have: Experience delivering AI/ML workloads in production
Nice to have: Knowledge of enterprise customer segments
Nice to have: Experience in specific technology domains such as software development, systems engineering, infrastructure, security, networking, data & analytics
Nice to have: Professional proficiency in French or German
Senior Software Engineer to join the growing AI organization, focusing on agentic runtime, evaluation/safety infrastructure, or customer-facing builders for human-AI coordination.
Compensation
For this role, the estimated base salary range is between $176,000 -$200,000.
Responsibilities
Drive the technical design, architecture, and end-to-end delivery of medium-to-large projects across our AI roadmap
Design robust, extensible, and performant systems that support agentic execution, prompt-driven automation, model orchestration, and strict enterprise-grade data boundaries
Solve complex technical problems by weighing technical debt, developer velocity, execution risk, and direct business goals
Anticipate customer and architectural risks early, breaking down complex, ambiguous product visions into clear engineering milestones and actionable tasks
Champion technical excellence, write high-leverage design docs, run meaningful retrospectives, establish testing norms, and mentor engineers across levels
Lead AI Engineer responsible for designing, building, and shipping generative AI systems and agentic solutions for Bain’s clients.
Responsibilities
Contribute to the design, development, and deployment of end-to-end generative AI systems, including multi-agent workflows and production-grade AI applications.
Build and iterate on multi-component AI pipelines such as Retrieval-Augmented Generation, fine-tuning, embedding generation, hybrid retrieval strategies, reasoning, tool use, and orchestration across AI workflows.
Build and contribute to agentic systems, applying 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.
Requirements
Nice to have: French language proficiency at C1 level or higher
Nice to have: experience mentoring peers
Nice to have: experience with ReAct, RLAIF, and other HITL + feedback loops
Nice to have: experience with hybrid or graph-based retrieval approaches
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