Lead, AI Engineering (Chicago)

General Information


Job Title


Lead, AI Engineering


Job ID


102641


Work Areas


Analytics, Data & Research, Management Consulting, Technology & Engineering


Employment Type


Permanent Full-Time


Location(s)


Atlanta, Austin, Boston, Chicago, Dallas, Houston, Los Angeles, New York, San Francisco, Seattle, Washington DC




Description & Requirements
What Makes Us A Great Place To WorkWe 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 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.About Bain AI, Insights & Solutions (AIS)Bain’s AI, Insights & Solutions (AIS) team works with clients to design and deliver AI-powered solutions that create measurable business impact. You’ll operate in multidisciplinary teams alongside Bain consultants, other experts in product, design, architecture and engineering, and client stakeholders, translating ambiguous business problems into robust AI applications that can be piloted, scaled, and adopted.The Impact You’ll HaveBain works with clients on board-level and executive priorities, helping deliver step-change results across growth, productivity, and resilience. In that context, AI is rarely a point solution. The most meaningful outcomes come from building AI as part of an integrated system that combines technology with redesigned processes, operating model changes, and adoption at scale across the organization.As an AI Engineer in AIS, you will build the technical core of these transformations and work as part of broader Bain consulting teams to move solutions from prototype to real adoption. The result is measurable impact at the company or enterprise level and, in many cases, helps clients set new performance standards for their industries.The RoleThe Lead AI Engineer will design, build, and ship generative AI systems and agentic solutions for Bain’s clients. You will contribute across the full development lifecycle — from early experimentation and prototyping through to production deployment — collaborating closely with senior engineers, product managers, and data scientists. This is a hands-on individual contributor role with growing influence on technical direction and an opportunity to begin mentoring more junior team members.You will have opportunities to work with major AI ecosystem partners through Bain’s partnerships, collaborating on real client deployments and helping shape how emerging capabilities are applied in enterprise settings.Bain offers significant learning and growth opportunities through the breadth and depth of problems we solve, the level of impact we help clients achieve, and our apprenticeship model. You will learn by doing, with support from experienced teammates, frequent feedback, and increasing responsibility over time.What You’ll DoContribute 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, including:Retrieval-Augmented Generation (RAG) Fine-tuning and parameter-efficient tuningEmbedding generation and optimizationHybrid retrieval strategies (vector, graph, keyword)Implement reasoning, tool use, function calling, and orchestration across AI workflowsBuild and contribute to agentic systems, applying sound engineering principles around separation of concerns, memory architecture, and tool integrationContribute across the full stack: model experimentation, evaluation design, and production system deploymentBuild and maintain APIs, microservices, CI/CD pipelines, and cloud-native deployments with attention to observability and reliabilitySupport and help build GenAIOps processes for automated testing, regression evaluation, latency monitoring, and continual improvementBalance performance, safety, responsible AI principles, and cost across system design:Implement guardrails, fallbacks, red-teaming strategies, and human-in-the-loop (HITL) workflowsPartner with global ethics teams to ensure alignment with Bain’s Responsible AI standardsBuild automated evaluation suites integrating user signals, continual learning cycles, and ongoing model updatesDesign and implement evaluation frameworks covering:Hallucination rate and factual consistencyRelevance and precision/recallLatency, throughput, and system-level performanceCost tracking and efficiencyPartner closely with product, engineering, data science, ethics, and infrastructure teams to build robust, compliant AI systemsContribute technical insights and communicate findings clearly to cross-functional stakeholders and, where relevant, clientsShare knowledge with peers and support a culture of technical learning around RAG, agents, prompt engineering, and AI safetyWhat We’re Looking For (Qualifications)3–5+ years in software engineering, ML engineering, or applied AI roles with hands-on building responsibilitiesDemonstrated experience shipping generative AI features or systems end-to-end, from prototyping through productionClear communication skills with the ability to explain technical concepts to non-technical collaborators and stakeholdersDemonstrated ability to collaborate effectively across engineering, product, and data science teams; some experience supporting or informally mentoring peers is a plusSolid prompt engineering and context engineering skills; familiarity with conversation design principlesWorking knowledge of evaluation design, experimentation frameworks, and data labeling strategies for LLM applicationsExperience with:RAG architectures (vector-based retrieval; exposure to hybrid or graph-based approaches is a plus)Agentic patterns (tool use, routing, memory management; multi-agent systems experience is a plus)ReAct, RLAIF, and other HITL + feedback loops.AI-Specific Tools & Frameworks - Orchestration frameworks, Vector and graph databases and Model + API ecosystemsStrong background in system design, architecture, and production-grade deploymentFamiliarity with cost and latency tradeoffs when working with LLM workloadsComfort operating in high-ambiguity environments with collaborative cross-functional teamsEagerness to grow into a technical leadership role and support junior team membersExperience in client-facing consulting or enterprise transformation environments is a strong plusWorking Model & TravelThis role requires a minimum of three 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.U.S. Compensation InformationCompensation for this role includes base salary, annual discretionary performance bonus, 401(k) plan with an annual employer contribution based on years of service and Bain’s best in class benefits package (details listed below).Some local governments in the United States require a good-faith, reasonable salary range be included in job postings for open roles. The estimated annualized compensation for this role is as follows:In New York City, California, Washington State, and Washington D.C, the good-faith, reasonable annualized full-time salary for this role is $203,500; In the state of Illinois, Georgia, Massachusetts, and Texas, the good-faith, reasonable annualized full-time salary for this role is $179,500. For all other locations, the good-faith, reasonable annualized full-time salary range for this role is commensurate with competitive geographic market rates for this role and will vary based on several factors including, but not limited to experience, education, licensure/certifications, training and skill level. Annual discretionary performance bonus This role may also be eligible for other elements of discretionary compensation 4.5% 401(k) company contribution, which increases after 3 years of service and is 100% vested upon start date Bain & Company's comprehensive benefits and wellness program is designed to help employees achieve personal independence, protection and stability in the areas most important to you and your family. Bain pays 100% individual employee premiums for medical, dental and vision programs, offering one of the most comprehensive medical plans for employees without impacting your paycheck Generous paid time off, including parental leave, sick leave and paid holidays Fully vested 401(k) company contribution Paid Life and Long-Term Disability insurance Annual fitness reimbursementsIt is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability
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