Build AI-powered products that help B2B teams convert market opportunity into booked revenue. Join the Coro team at Bain & Co. to help create the next generation of Coro products with AI and agentic capabilities. This onsite role in Chicago, IL focuses on designing and implementing LLM-driven features, agentic workflows, retrieval and knowledge pipelines, and ML/GenAIOps for secure enterprise deployment and reliable delivery.
Compensation: USD 128,500 - 171,500 per year, plus an annual discretionary performance bonus and Bain’s benefits package. Medical, dental and vision premiums are covered 100% for individual employees.
What you’ll do
- Design and develop GenAI applications such as copilots, workflow automation, and decision support for commercial teams using modern LLM stacks.
- Implement agentic workflows where they add clear value, including tool use, multi-step execution, and human-in-the-loop controls, with attention to reliability, safety, and clear failure modes.
- Build advanced search and retrieval systems across diverse data structures and stores, including hybrid search, vector stores, and graph databases/knowledge graphs, covering indexing strategies, metadata design, relevance tuning and reranking, freshness, caching, access controls, and source attribution.
- Develop robust agent capabilities across context engineering, short-term and long-term memory/state management, orchestration, routing, and tool integration patterns.
- Integrate solutions into enterprise workflows via APIs and data systems and collaboration tools, 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 including data preparation, feature engineering, model selection, training, validation and testing, and performance analysis, using classical ML and deep learning as appropriate (including sequence, text, and image models when relevant).
- Create reproducible training and evaluation pipelines with versioning, experiment tracking, robust validation, and clear documentation.
- Ship AI services across the full SDLC: build, test, deploy, monitor, and iterate.
- Apply MLOps and GenAIOps practices including CI/CD, reproducibility, environment parity, and versioning for models, prompts, and agents to support operational readiness.
- Build evaluation and observability for GenAI and agentic systems using tracing/instrumentation, regression test suites, automated scoring where appropriate, and iteration loops for prompt and policy optimization.
- Design for secure enterprise deployment with access controls, auditability, careful data handling for sensitive and PII data, and responsible AI guardrails.
- Create reusable components and accelerators such as templates, evaluation harnesses, connectors, and orchestration patterns that scale across client contexts.
- Collaborate and communicate with technical and non-technical stakeholders by leading working sessions, presenting recommendations, and writing crisp technical documentation, including working directly with clients and Bain consultants to prioritize critical technical decisions.
- Support proposal shaping and scoping with effort sizing, architecture options, risk assessment, and delivery roadmaps.
What you bring
- 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 Python skills and experience building APIs/services (REST/gRPC) integrated into enterprise systems.
- Hands-on experience building LLM-powered applications with delivery considerations including latency, cost, reliability, and security.
- Experience building advanced retrieval/search (hybrid retrieval, vector search, reranking) and comfort working across multiple data stores such as vector, graph, and relational/document/search systems.
- Experience implementing agentic patterns (context management, tool integration, orchestration, and memory/state handling) using modern frameworks (LangGraph, OpenAI Agents SDK, Pydantic AI) or custom agent loops, with strong judgment on when agentic approaches fit.
- Experience creating reusable skills/tools/services for agent use (including MCP) and schema validation (e.g., Pydantic) to enforce reliable data contracts.
- Strong engineering practices across testing, code review, version control, and CI/CD, plus performance profiling.
- Experience deploying and operating services on AWS, GCP, and/or Azure with environment management, reliability, observability, and scaling.
- Experience with Docker and Kubernetes (or equivalent orchestration) and operating services in production.
- Proven ability to implement security, privacy, and governance requirements for AI systems including authentication/authorization, access controls, and PII/sensitive data handling.
- Experience training, validating, and testing ML models with strong understanding of overfitting, generalization, and evaluation methodology.
- Practical experience with feature engineering and data preprocessing for real-world datasets.
- Familiarity with deep learning frameworks (PyTorch/TensorFlow) and ML lifecycle tooling (experiment tracking, model registry, feature store concepts).
- Ability to operate in ambiguity and deliver outcomes independently or with a collaborative team.
- Excellent interpersonal and communication skills to explain technical decisions, tradeoffs, and results to mixed audiences, with strong stakeholder management and comfort working directly with clients.
Technologies you may use
Python, REST, gRPC, LLM, LangGraph, OpenAI Agents SDK, Pydantic AI, Pydantic, MCP, AWS, GCP, Azure, Docker, Kubernetes, PyTorch, TensorFlow, CI/CD, vector stores, graph databases, knowledge graphs.
Benefits
- Medical, dental and vision programs (Bain pays 100% individual employee premiums).
- 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.
- 401(k) company contribution: 4.5% 401(k) company contribution, increases after 3 years of service, and is 100% vested upon start date.
- Annual discretionary performance bonus.
About Bain’s Commercial Excellence and Coro
Bain’s B2B Commercial Excellence practice helps clients develop a clear go-to-market strategy by understanding market opportunity, designing effective sales coverage and capacity models, and creating an industrialized sales execution capability. Coro’s software and data solutions are an innovative and increasingly critical part of this approach.
The Coro business unit brings together Bain’s proprietary suite of SaaS and DaaS tools, including cloud-based software, online capability assessments, and advanced analytics, focused on enabling Commercial Excellence for B2B companies.
Impact you’ll have
- Bain’s Commercial Excellence work helps B2B companies turn market opportunity into booked revenue through sharper go-to-market strategy, better sales coverage and capacity, and industrialized execution.
Preferred background
- MBA, or PhD in a technical field.
- Background in consulting, professional services, or B2B analytics environments.
- Experience working with major AI ecosystem partners on real client deployments.
