Expert Consultant, Coro, AI Engineer

Join Bain & Company in Washington, DC, onsite, as an AI Engineer on the Coro team. You will help build GenAI powered tools and data-driven capabilities for B2B Commercial Excellence, designing, developing, and deploying AI solutions from proofs of concept to production in a client-facing consulting setting. This role centers on agentic workflows, retrieval pipelines, and ML models that drive business value for our clients.

This position offers a compelling benefits package and a collaborative culture that supports growth, impact, and professional development. You will work closely with Bain consultants and client teams to deliver practical AI solutions, balancing quality, speed, privacy, and adoption in enterprise environments.

Responsibilities

• Design and build GenAI applications such as copilots, workflow automation, and decision-support tools for commercial teams using modern large language model stacks.
• Implement agentic workflows with value, including tool use, multi-step execution, and human-in-the-loop controls, emphasizing reliability, safety, and clear failure modes.
• Design and construct advanced search, retrieval, and knowledge pipelines across diverse data stores, covering indexing, metadata, relevance tuning, freshness, caching, access controls, and source attribution.
• Develop robust agent capabilities including 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) while balancing quality, latency, cost, privacy, and adoption.
• Translate ambiguous client needs into clear technical requirements, tradeoffs, and delivery plans.
• Deliver end-to-end ML solutions: data preparation, feature engineering, model selection, training, validation, testing, and performance analysis.
• Apply suitable methods spanning classical ML and deep learning, including sequence, text, and image models where relevant.
• Create reproducible training and evaluation pipelines with versioning, experiment tracking, robust validation, and documentation.
• Demonstrate fluency with modern deep learning concepts, including transformer fundamentals and LLM pre-training versus post-training approaches.
• Write clean, testable, maintainable 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, and iteration loops for prompt and policy optimization.
• Design for secure enterprise deployment: access controls, auditability, handling of sensitive and PII data, and responsible AI guardrails.
• Develop reusable components and accelerators that scale across client contexts, including templates, evaluation harnesses, connectors, and orchestration patterns.
• Communicate clearly with technical and non-technical stakeholders; lead working sessions, present recommendations, and document technical approaches succinctly.
• Collaborate with Bain consultants to prioritize technical decisions that unlock business value and 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 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 and search systems (hybrid retrieval, vector search, reranking) and working across vector, graph, relational, document, and search data stores.
• Experience implementing agentic patterns (context management, tool integration, orchestration, memory/state handling) with modern frameworks (LangGraph, OpenAI Agents SDK, Pydantic AI) or custom agent loops; solid judgment on when to apply agentic approaches.
• Experience creating reusable skills, tools, and services for agent use, with schema validation (Pydantic) to enforce reliable 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, including environment management, reliability, observability, and scaling.
• Experience with Docker and Kubernetes (or equivalents) and operating services in production (debugging, performance, resilience).
• Proven ability to meet security, privacy, and governance requirements for AI systems (authentication/authorization, access controls, PII handling, enterprise risk controls).
• Experience training, validating, and testing ML models with 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 (classical and deep learning) and the ability to select methods aligned with business constraints.
• Familiarity with deep learning frameworks (PyTorch/TensorFlow) and ML lifecycle tooling (experiment tracking, model registry, feature store concepts).
• Ability to operate effectively in ambiguous and complex environments, manage priorities, and deliver outcomes independently or with a team.
• Excellent interpersonal and communication skills; able to explain technical decisions 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
• Docker
• Kubernetes
• AWS, GCP, Azure
• PyTorch, TensorFlow
• MCP

Compensation and Benefits

• Base salary range of USD 128,500 to 171,500 annually, with variation by location and experience for states including Massachusetts, New York, District of Columbia, Georgia, Illinois, Texas, Washington, and California.
• Annual discretionary performance bonus.
• 4.5% 401(k) company contribution, increasing after three years of service, fully vesting on start date.
• Bain pays 100% of individual employee premiums for medical, dental, and vision coverage.
• Generous paid time off including parental leave, sick leave, and holidays.
• Paid life and long-term disability insurance.
• Annual fitness reimbursements.
• Other comprehensive benefits and wellness programs in line with Bain’s offerings.