Director, AI Engineering - Tech Lead

Boston, Chicago, London, Sao Paulo, Warsaw

Description & Requirements

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. Extraordinary teams are at the heart of our business strategy, requiring 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 will be part of a team building Bain’s integrated suite of agentic decisioning tools that gives large organizations always-on intelligence across their most important growth decisions. The role sits at an intersection few organizations can offer: the analytical depth and client access of a top-tier consultancy, the technical ambition of a product company, and engineering work at the frontier of applied AI. You will work inside Bain’s standing product team, building software that helps the world’s largest companies answer the questions that drive their business: where to invest, where to focus, and how to win.

The impact of what you build is direct and immediate, and the platform compounds in value with every release. The platform has two layers working together: an agentic core and a set of decision modules, each solving a distinct commercial problem. The build lifecycle is connected to the real world: as case teams work alongside clients across industries and geographies, that feedback flows straight back to engineering and into the product. Every client engagement makes the platform smarter, broader, and more resilient. This is a startup inside an established company. You get genuine early-stage ownership and real influence over architecture and product direction, backed by Bain’s global scale, client relationships, and leadership commitment; the pace of a startup with the runway of a global firm.

We are looking for engineers who see how to make a product better and bring that instinct to every sprint without being asked, and who are comfortable with problems that do not have a known answer. The work involves real-time decision engines, cloud-native infrastructure, and data problems with no off-the-shelf answer. Experience with agentic systems matters: tool and context protocols such as MCP, evaluation harnesses, memory design, and entity resolution across messy enterprise data. This is applied AI in production, at scale, with real users depending on what you build. The field is moving quickly and the team is built to move with it, so the willingness to keep learning counts for as much as what you already know.

Where You’ll Fit Within the Team

The AI Engineer is a core builder of the Growth AI Performance System platform’s Agentic Core and Interface: the shared foundation that all three product modules are built on. This is not a module-level role; you are building the central intelligence layer: the agentic workflows, retrieval and knowledge pipelines, tool integrations, and interface infrastructure that every product in the suite depends on. Moving solutions from early POC and MVP through to scaled production deployments, you are responsible for the reliability, quality, and coherence of the systems that real client teams use every day.

You will work across the platform and product modules focused on marketing ROI, brand, and pricing strategy, translating the analytical and commercial questions that client teams are trying to answer into reliable, production-grade agentic systems that deliver those answers at scale. The role requires both deep technical capability and genuine client awareness. You will engage directly with consulting teams and, at times, with senior stakeholders, presenting how the Agentic Core works, translating system design decisions into business terms, and using that feedback to make the platform better.

The build loop here is tight: client engagement informs engineering, and every release makes the suite more capable. This role sits at the intersection of research and production engineering. The problems are rarely solved by off-the-shelf tooling: they require judgment about when agentic approaches add real value, how to build systems that fail gracefully, and how to measure quality in ways that matter to real users on real client engagements.

What You’ll Do

• Building the Agentic Core
• Build and own core components of the Growth AI Performance System Agentic Core, including multi-agent orchestration frameworks, tool registries, shared memory and state management, and the interface infrastructure that surfaces platform capabilities to users.
• Build AI applications for enterprise use cases across the full delivery lifecycle, from rapid POCs and MVPs through to scaled production deployments, designing AI workflows that execute multi-step tasks reliably and safely.
• Implement agentic patterns with strong judgment about when they add real value; build robust agent capabilities including context engineering, memory and state management, reasoning and planning, reflection, orchestration, routing, tool selection, function calling, and tool integration.
• Design and build advanced retrieval and knowledge pipelines across diverse data structures, covering embedding generation and optimization, indexing strategies, metadata design, relevance tuning, caching, access controls, and source attribution.
• Apply fine-tuning and parameter-efficient tuning techniques where they measurably outperform prompting and retrieval alone.
• Integrate platform capabilities into enterprise environments, balancing quality, latency, cost, privacy, and adoption.

Engineering quality and operations

• Engineer for real delivery across the full software development lifecycle: write clean, testable, maintainable code; build APIs and microservices for cloud-native deployment.
• Build evaluation and observability for the Agentic Core: tracing and instrumentation of agentic execution, regression test suites, automated scoring pipelines, and iteration loops for prompt and policy optimization.
• Design evaluation frameworks that track hallucination rate and factual consistency, relevance and retrieval precision/recall, latency and throughput, and cost per task.
• Apply data science and ML skills as needed to materially improve platform performance or reliability.
• Design for secure enterprise deployment: access controls, auditability, responsible handling of sensitive data, and responsible AI guardrails.

About You

Technical

• Strong proficiency in Python and experience building and integrating production services.
• Experience designing and implementing agentic workflows and multi-step LLM pipelines.
• Experience building retrieval and knowledge pipelines across vector, keyword, hybrid, and graph-based data structures.
• Proficiency with MLOps and AIOps practices.
• Advanced prompt engineering, context engineering, and conversation design.
• Solid system design and architecture skills.
• Ability to apply data science and ML skills to improve system performance.
• Strong engineering fundamentals.
• Native AI fluency in day-to-day engineering.
• Demonstrated commitment to responsible AI practices.

Experience

• 10 or more years in software engineering or applied AI roles.
• Track record of shipping production AI or ML systems end-to-end.
• Experience contributing to complex, multi-stack generative AI programs.
• Experience working in agile, cross-functional product or consulting-adjacent environments.
• Direct experience engaging with clients or senior business stakeholders in a technical capacity.

Education

• Associate’s degree / Bachelor’s degree in computer science, engineering, mathematics, or a related technical field.

U.S. Compensation Information

Compensation 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.

Some local governments in the United States require a good-faith, reasonable salary range to be included in job postings for open roles. The estimated annualized compensation for this role is as follows:

• In Massachusetts, the good-faith, reasonable annualized full-time salary range for this role is between $235,750 - $282,500.
• In Illinois, the good-faith, reasonable annualized full-time salary range for this role is between $225,750 - $270,500.

This role may also be eligible for other elements of discretionary compensation.

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.

Paid Life and Long-Term Disability insurance.

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.