Joining Bain & Company’s Coro unit as an Expert Consultant AI Engineer places you at the forefront of client-facing innovation, blending strategic insight with hands-on development of GenAI and ML capabilities for B2B go-to-market solutions. Based onsite in San Francisco, you will design and deploy AI-powered tools that drive measurable business outcomes while guiding clients through complex technical tradeoffs and implementation decisions.
Responsibilities
- Develop AI-powered tools and products that deliver tangible business value
- Design and deploy GenAI applications such as copilots, workflow automation, and decision support for commercial teams using modern LLM stacks
- Implement agentic workflows with clear value, including tool use, multi-step execution, and human-in-the-loop controls, prioritizing reliability, safety, and well-defined failure modes
- Architect advanced search, retrieval, and knowledge pipelines across diverse data structures and stores (hybrid search, vector stores, graph databases/knowledge graphs, and traditional data platforms), covering indexing, metadata, relevance tuning, freshness, caching, access controls, and source attribution
- Build robust agent capabilities such as context engineering, memory and state management, orchestration, routing, and tool integration patterns
- Integrate AI solutions into enterprise environments and workflows (APIs, data systems, collaboration tools), balancing quality, latency, cost, privacy, and adoption
- Translate ambiguous client needs into clear technical requirements, tradeoffs, and delivery plans
- Develop and apply data science and machine learning capabilities, delivering end-to-end ML solutions
- Handle data preparation, feature engineering, model selection, training, validation and testing, and performance analysis
- Apply appropriate methods across classical ML and deep learning, including sequence, text, and image models when relevant
- Create reproducible training and evaluation pipelines with versioning, experiment tracking, robust validation, and documentation
- Maintain fluency with modern deep learning concepts, including transformer fundamentals and distinctions between pre-training and fine-tuning approaches
- Engineer for real delivery, writing clean, testable, maintainable code and shipping AI services through the full SDLC
- Implement MLOps and GenAIOps practices: CI/CD, reproducibility, environment parity, model/prompt/agent versioning, and operational readiness
- Build evaluation and observability for GenAI and agentic systems: tracing, instrumentation, regression tests, automated scoring, and iterative prompt/policy optimization
- Design for secure enterprise deployment with access controls, auditable data handling for sensitive/PII data, and responsible AI guardrails
- Create reusable components and accelerators that scale across client engagements
- Thrive in a client-facing consulting environment, communicating clearly with technical and non-technical stakeholders, leading sessions, and documenting recommendations
- Collaborate with Bain consultants to prioritize critical technical decisions that unlock business value
- Support proposal shaping and scoping, including effort sizing, architecture options, risk assessment, and delivery roadmaps
Requirements
- Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience
- 3-5+ years of professional AI/ML engineering experience with strong backend fundamentals
- Proficiency in Python and experience building APIs/services (REST/gRPC) and integrating with enterprise systems
- Hands-on experience delivering LLM-powered applications with attention to latency, cost, reliability, and security
- Experience building advanced retrieval/search systems (hybrid retrieval, vector search, reranking) and comfort across vector, graph, relational, document, and search data stores
- Experience implementing agentic patterns (context management, tool integration, orchestration, memory/state handling) using modern frameworks or custom agent loops, with good judgment on when to apply agentic approaches
- Experience creating reusable skills, tools, and services (including MCP) for agent use, with schema validation to enforce data contracts
- Strong engineering practices: testing, code review, version control, CI/CD, and performance profiling
- Experience deploying and operating services on AWS, GCP, and/or Azure with reliable, observable, scalable deployments
- Experience with Docker and Kubernetes and operating services in production (debugging, performance, resilience)
- Proven ability to implement security, privacy, and governance requirements for AI systems (authentication/authorization, access controls, PII handling, enterprise risk controls)
- Experience training, validating, and testing ML models; solid understanding of overfitting, generalization, and evaluation methodology
- Practical experience with feature engineering and data preprocessing for real-world datasets
- Familiarity with a broad set of ML algorithms and the ability to select methods that align with business and data constraints
- Familiarity with deep learning frameworks (PyTorch/TensorFlow) and ML lifecycle tooling (experiment tracking, model registry, feature store concepts)
- Proven ability to operate in ambiguity and complexity, manage priorities, and deliver outcomes independently or with a team
- Excellent interpersonal and communication skills, able to explain technical decisions, tradeoffs, and results to mixed audiences
- Strong stakeholder management skills and comfort working directly with clients
Technologies
- Python
- REST
- gRPC
- LangGraph
- OpenAI Agents SDK
- Pydantic AI
- MCP
- PyTorch
- TensorFlow
- AWS
- GCP
- Azure
- Docker
- Kubernetes
- Vector stores
- Graph databases
- Knowledge graphs
- Pydantic
Benefits
- Bain pays 100% of individual employee premiums for medical, dental, and vision programs
- 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 reimbursements
- 4.5% 401(k) company contribution, increasing after 3 years of service and 100% vesting on start date
U.S. Compensation Information
Compensation for this role includes base salary, an annual discretionary performance bonus, and a 401(k) plan with company contributions and Bain’s comprehensive benefits package. The base salary range is USD 128,500 to 171,500 per year, with placement within this range varying by experience, education, and skill level. Some states require disclosure of a good-faith salary range; for Massachusetts, New York, District of Columbia, Georgia, Illinois, Texas, Washington, and California, the range is between 128,500 and 171,500 USD annually. The role may be eligible for other elements of discretionary compensation, in addition to the 4.5% 401(k) company contribution (which increases after 3 years and is 100% vested at start). Bain offers a robust benefits and wellness program, including employer-paid premiums for medical, dental, and vision, paid time off, fully vested 401(k), life and disability coverage, and fitness reimbursements. For all other locations, compensation is commensurate with competitive geographic market rates. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. Please submit your resume/CV in English to be considered for this role.
Preferred
- MBA or PhD in a technical field
- Background in consulting, professional services, or B2B analytics environments
- Experience collaborating with major AI ecosystem partners on real client deployments
