This role is for an AI Engineer to join Bain & Co's Coro team in Houston, TX, onsite. You will design and implement GenAI enabled features and agentic workflows across rapid proofs of concept to production deployments, turning client data into structured analytics and synthesized outputs.
Responsibilities
- Design and develop GenAI applications such as copilots, workflow automation, and decision support for commercial teams using modern large language model stacks.
- Implement agentic workflows that add clear value, including tool use, multi-step execution, and human in the loop controls, with emphasis on reliability, safety, and identifiable failure modes.
- Design and build advanced search, retrieval, and knowledge pipelines across diverse data structures and stores, covering indexing strategies, metadata design, relevance tuning and reranking, freshness, caching, access controls, and source attribution.
- Build robust agent capabilities including context engineering, memory and state management, orchestration, routing, and tool integration patterns.
- Integrate solutions into enterprise environments and workflows via APIs, data systems, and collaboration tools, balancing quality, latency, cost, privacy, and adoption.
- Translate ambiguous client needs into clear technical requirements, tradeoffs, and delivery plans.
- Develop end-to-end ML solutions, including data preparation, feature engineering, model selection, training, validation and testing, and performance analysis.
- Apply appropriate methods for the problem, spanning 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 comprehensive documentation.
- Demonstrate fluency with modern deep learning concepts, including transformer fundamentals and LLM pre-training versus post-training concepts such as instruction tuning and preference optimization.
- 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 and prompt versioning, and operational readiness.
- Build evaluation and observability for GenAI and agentic systems: tracing, instrumentation, regression test suites, automated scoring where appropriate, and iteration loops for prompt and policy optimization.
- Design for secure enterprise deployment: access controls, auditability, data handling for sensitive and PII data, and responsible AI guardrails.
- Build 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 details succinctly.
- Collaborate with Bain consultants to prioritize 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 with strong backend engineering fundamentals.
- Strong proficiency in Python and experience building APIs or services (REST or gRPC) and integrating with enterprise systems.
- Hands-on experience building 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 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 judgment about when to use agentic approaches.
- Experience creating reusable skills, tools, and services for agent use, with schema validation 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 equivalent orchestration and operating services in production.
- Proven ability to implement security, privacy, and governance requirements for AI systems, including authentication/authorization, access controls, PII handling, and enterprise risk controls.
- Experience training, validating, and testing ML models with an understanding of overfitting, generalization, and evaluation methodologies.
- 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 ability to select methods that fit business and data constraints.
- Familiarity with deep learning frameworks (PyTorch, TensorFlow) and ML lifecycle tooling (experiment tracking, model registry, feature store concepts).
- 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; comfort working directly with clients.
- MBA or PhD in a technical field (preferred).
- Background in consulting, professional services, or B2B analytics environments.
- Experience collaborating with major AI ecosystem partners on real client deployments.
Technologies
- Python
- REST
- gRPC
- LangGraph
- OpenAI Agents SDK
- Pydantic AI
- MCP
- PyTorch
- TensorFlow
- Docker
- Kubernetes
- AWS
- GCP
- Azure
- Graph databases
- Vector stores
- Knowledge graphs
Benefits
- Bain pays 100% of individual employee premiums for medical, dental, and vision programs, maintaining strong coverage without payroll impact
- 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, increasing after three 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 employer contributions based on years of service. Bain offers a comprehensive benefits package.
In the states listed below, the good-faith, reasonable annualized full-time salary range is $128,500 to $171,500. Placement within this range depends on factors such as experience, education, training, and skill level:
- Massachusetts
- New York
- District of Columbia
- Georgia
- Illinois
- Texas
- Washington
- California
The role may be eligible for other elements of discretionary compensation, in addition to a 4.5% 401(k) company contribution that increases after three years of service and is 100% vested upon start date.
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