GenAI Engineer for Enterprise AI & Agentic Workflows

Bain & Co.; Houston (TX); On-site; USD 129,000 - 172,000; Full time

Benefits offered by this job

Premium medical coverage

Generous PTO

401(k) plan with vesting

Life and Disability insurance

Job summary

Bain & Company is seeking an AI Engineer to design and deploy GenAI powered features and agentic workflows from rapid proofs of concept to production, turning client data into structured analytics and synthesized outputs.

The role focuses on building GenAI applications, retrieval systems, and robust ML pipelines while balancing latency, cost, and security in enterprise environments. Collaborative problem solving with Bain consultants is expected.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or related field, or equivalent practical experience.
• 3–5+ years of professional AI/ML engineering experience (or equivalent).
• Strong proficiency in Python and experience building APIs / services (REST / 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 / 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.

Responsibilities

• Design and build GenAI applications including copilots, workflow automation, and decision-support for commercial teams using modern large language model stacks.
• Implement agentic workflows with clear 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 structures and stores with indexing, metadata, relevance tuning, freshness, caching, access controls, and source attribution.
• Develop robust agent capabilities such as context engineering, memory and state management, orchestration, routing, and tool integration patterns.
• Integrate 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 including data preparation, feature engineering, model selection, training, validation and testing, and performance analysis.
• Apply methods 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 documentation.
• Demonstrate fluency with modern deep learning concepts, transformer fundamentals, and LLM pre-training versus post-training concepts.
• 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 where appropriate, and iteration loops for prompts 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.
• Communicate clearly with technical and non-technical stakeholders; lead working sessions, present recommendations, and write crisp technical documentation.
• Collaborate with Bain consultants to prioritize critical technical decisions that unlock business value.
• Support proposal shaping and scoping: effort sizing, architecture options, risk assessment, and delivery roadmaps.

Skills

Python

Backend engineering

AI/ML

Communication

Stakeholder management

Education

Bachelor's degree in CS or related field

MBA or PhD in technical field

Tools

REST

gRPC

LangGraph

OpenAI SDK

Pydantic AI

MCP

PyTorch

TensorFlow

Docker

Kubernetes

AWS

GCP

Azure

Graph databases

Vector stores

Job description

Bain & Company is seeking an AI Engineer to design and deploy GenAI powered features and agentic workflows from rapid proofs of concept to production, turning client data into structured analytics and synthesized outputs.

The role focuses on building GenAI applications, retrieval systems, and robust ML pipelines while balancing latency, cost, and security in enterprise environments. Collaborative problem solving with Bain consultants is expected.