Expert Consultant, Coro, AI Engineer

About the role

Bain is a consulting firm known for its excellence and innovation. We are currently the top-ranked consulting firm on Glassdoor's Best Place to Work list, having achieved this status seven times.

Responsibilities

• Build AI-powered tools and products that drive real business outcomes
• Design and develop GenAI applications (e.g., copilots, workflow automation, decision support for commercial teams)
• Implement agentic workflows where they add clear value (e.g., tool use, multi-step execution, human-in-the-loop controls)
• Create advanced search, retrieval, and knowledge pipelines across diverse data structures and stores
• Build robust agent capabilities including context engineering, memory and state management, orchestration, routing, and tool integration patterns
• Integrate solutions into enterprise environments and workflows
• Translate ambiguous client needs into clear technical requirements, tradeoffs, and delivery plans
• Apply data science and machine learning capabilities
• Deploy and operate services on AWS, GCP, and Azure
• Implement security, privacy, and governance requirements for AI systems
• Work effectively with Bain consultants to prioritize the critical few technical decisions that unlock business value
• Support proposal shaping and scoping

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 engineering fundamentals
• Strong proficiency in Python and experience building APIs / services (e.g., REST / gRPC) and integrating with enterprise systems
• Hands-on experience building LLM-powered applications with delivery considerations (latency, cost, reliability, security)
• Experience building advanced retrieval / search systems (e.g., hybrid retrieval, vector search, reranking)
• Experience implementing agentic patterns (context management, tool integration, orchestration, and memory / state handling)
• Experience creating reusable skills, tools, and services (including MCP) for agent use, with schema validation (e.g., Pydantic) to enforce reliable data contracts
• Strong engineering practices: testing, code review, version control, CI / CD, and performance profiling
• Cloud, platform, and production delivery experience
• Experience deploying and operating services on AWS, GCP, and / or Azure (environment management, reliability, observability, scaling)
• Experience with Docker and Kubernetes (or equivalent orchestration) 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 / sensitive data handling, enterprise risk controls)
• Breadth of knowledge across data science and machine learning
• Experience training, validating, and testing ML models; strong understanding of overfitting, generalization, and evaluation methodology
• Familiarity with a broad set of ML algorithms (classical ML and deep learning), and the ability to choose methods that match the business and data constraints
• Familiarity with deep learning frameworks (e.g., PyTorch / TensorFlow) and ML lifecycle tooling (e.g., experiment tracking, model registry, feature store concepts)
• Delivery mindset and consulting skills
• Proven ability to operate in ambiguity and complexity, manage priorities, and deliver outcomes independently or with a collaborative team
• Excellent interpersonal and communication skills, able to explain technical decisions, tradeoffs, and results to mixed audiences
• Strong stakeholder management skills; comfort working directly with clients

Qualifications

• Core engineering and AI application skills

Skills

• Python
• REST / gRPC
• LLM-powered applications
• Advanced retrieval / search systems
• Agentic patterns
• Reusable skills, tools, and services
• Deep learning frameworks
• ML algorithms
• Cloud, platform, and production delivery experience
• Docker and Kubernetes
• Security, privacy, and governance requirements for AI systems
• Data science and machine learning
• Delivery mindset and consulting skills
• Interpersonal and communication skills

Benefits

• 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

Pay

• Estimated annualized compensation range: $128,500 - $171,500

Schedule

• Full-time

U.S. Compensation Information

The estimated annualized compensation for this role is as follows:

• In Massachusetts, New York, District of Columbia, Georgia, Illinois, Texas, Washington, and California, the good-faith, reasonable annualized full-time salary range for this role is between $128,500-$171,500; placement within this range 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 reimbursements