Onsite in Palo Alto, this Expert Consultant on Bain's Coro team leads GenAI and agentic AI initiatives to empower Coro's SaaS and data tools for B2B Commercial Excellence. The role spans the full lifecycle from early proofs of concept to production deployments, translating client needs into scalable AI capabilities that deliver measurable business value.
Responsibilities
- Develop AI powered tools and products that drive tangible business outcomes
- Design and implement GenAI applications such as copilots, workflow automation, and decision support for commercial teams using modern large language model stacks
- Create agentic workflows with clear value, including tool usage, multi-step execution, and human in the loop controls, prioritizing reliability, safety, and clear 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 (short- and long-term), 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 precise technical requirements, tradeoffs, and delivery plans
- Develop and apply data science and machine learning capabilities
- Deliver end-to-end ML solutions: data preparation, feature engineering, model selection, training, validation and testing, and performance analysis
- Choose appropriate methods spanning classical ML and deep learning, including sequence, text, and image models when relevant
- Establish reproducible training and evaluation pipelines with versioning, experiment tracking, robust validation, and clear documentation
- Demonstrate fluency with modern deep learning concepts, covering transformer fundamentals and distinctions between pre-training and post-training approaches (e.g., instruction tuning, preference optimization)
- Write clean, testable code and ship AI services through the full SDLC: build, test, deploy, monitor, and iterate
- 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 test suites, automated scoring where appropriate, and loops for prompt and policy refinement
- Design for secure enterprise deployment: access controls, auditability, handling of sensitive and PII data, and responsible AI guardrails
- Develop reusable components and accelerators (templates, evaluation harnesses, connectors, orchestration patterns) that scale across client contexts
- Thrive in a client-facing consulting setting
- Communicate clearly with both technical and non-technical stakeholders; lead workshops, present recommendations, and maintain precise technical documentation
- Collaborate with Bain consultants to focus on the critical technical decisions that unlock business value
- Support proposal shaping and scoping through 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 (or equivalent), with strong backend fundamentals
- Strong Python proficiency 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 working across multiple data stores (vector, graph, relational, document, search)
- Experience implementing agentic patterns (context management, tool integration, orchestration, memory / state handling) with modern frameworks (e.g., LangGraph, OpenAI Agents SDK, Pydantic AI) or custom agent loops, and sound judgment on applicability
- Experience creating reusable skills, tools, and services for agent use, with schema validation (e.g., Pydantic) to enforce reliable data contracts
- Strong engineering practices: testing, code reviews, version control, CI/CD, and performance profiling
- Experience deploying and operating services on AWS, GCP, or Azure (environment management, reliability, observability, scaling)
- Experience with Docker and Kubernetes (or equivalent orchestration) and operating production services (debugging, performance, resilience)
- Proven ability to implement security, privacy, and governance requirements for AI systems (authentication / authorization, access controls, PII / sensitive data handling, risk controls)
- Experience training, validating, and testing ML models; strong 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 (classical ML and deep learning) and the ability to align methods 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; ability to explain technical decisions, tradeoffs, and results to diverse audiences
- Strong stakeholder management; comfortable working directly with clients
Technologies
- Python
- REST
- gRPC
- LangGraph
- OpenAI Agents SDK
- Pydantic AI
- PyTorch
- TensorFlow
- AWS
- GCP
- Azure
- Docker
- Kubernetes
- MCP
Benefits
- Bain pays 100% of individual employee premiums for medical, dental, and vision, offering a comprehensive plan with no payroll deduction
- Generous paid time off, including parental leave, sick leave, and holidays
- Fully vested 401(k) company contribution
- Paid life and long-term disability insurance
- Annual fitness reimbursements
- 4.5% 401(k) company contribution, which increases after 3 years and is 100% vested upon start date
- Annual discretionary performance bonus
U.S. Compensation Information
Compensation for this role includes base salary, an annual discretionary performance bonus, and a 401(k) plan with employer contributions that increase with years of service, along with Bain’s comprehensive benefits package.
In the states listed below, the estimated full-time annual range is $128,500 to $171,500, with final placement based on experience, education, training, and skill level: Massachusetts, New York, District of Columbia, Georgia, Illinois, Texas, Washington, and California.
The compensation package also features the annual discretionary performance bonus and a 4.5% 401(k) company contribution, which increases after 3 years of service and is 100% vested upon start date.
