AI Platform Senior Lead

Job Title: AI Platform Senior Lead

Location: Chicago, IL (hybrid)

Employment Type: Permanent, full-time (exempt)

Target Compensation: $150,000 to $210,000 + 8% Bonus

About The Company

Our client is a leading global law firm serving businesses, financial institutions and other organizations across a broad range of industries. Data & AI is a strategic priority for the firm, supported by a dedicated cross-functional organization of roughly 100 professionals spanning Data Engineering, AI Engineering, Product Management, UX, Data Governance, Business Intelligence and Program Management. The firm is actively investing in the development, evaluation, integration and responsible adoption of emerging AI technologies, and the team is building the next generation of enterprise AI capabilities used daily by lawyers and business professionals.

Job Summary

We are seeking an AI Platform Senior Lead to own the technical foundation on which the firm's AI products are built. This is a senior individual-contributor and technical leadership role focused on the platform layer: model integration and orchestration, retrieval and grounding infrastructure, evaluation and observability tooling, and the guardrails that make enterprise AI safe to deploy. The role partners closely with AI Engineering on product delivery, with Data Engineering on the underlying data platform, and with Product Management and Data Governance on what gets built and how it is controlled.

This is a strong opportunity for an engineer who wants to set technical direction for enterprise AI while it is still being defined, rather than maintaining a platform someone else designed.

Key Responsibilities

Own the architecture and technical direction of the enterprise AI platform, including model access, orchestration, retrieval and grounding services.
Design and build the integration layer between foundation models, internal data sources and the firm's AI applications.
Establish evaluation infrastructure - offline test suites, golden datasets, regression testing and quality metrics - so model and prompt changes can be measured rather than guessed at.
Build observability, logging, cost tracking and monitoring for AI workloads in production.
Implement responsible-AI guardrails covering access control, data handling, confidentiality, auditability and output safety, in partnership with Data Governance and Information Security.
Set engineering standards, design patterns and reusable frameworks that AI Engineering teams build against.
Lead technical design sessions and own code review for platform components.
Evaluate emerging models, tools and vendor platforms, and make build-versus-buy recommendations with a clear technical rationale.
Partner with Product Management to translate product requirements into platform capabilities.
Mentor engineers across the AI and data teams and raise the technical bar on AI engineering practice.
Troubleshoot complex issues across the AI stack, from retrieval quality to latency and cost.

Required Qualifications

Bachelor's degree in Computer Science, Engineering, Data Science or a related field.
Significant hands-on software or data engineering experience, including senior technical ownership of a platform or infrastructure area.
Demonstrated experience building production applications on large language models - retrieval-augmented generation, tool and function calling, agentic workflows, or comparable patterns.
Strong proficiency in Python, and solid SQL.
Experience with model orchestration and AI application frameworks, and with vector or hybrid search infrastructure.
Practical experience designing evaluation and testing approaches for non-deterministic systems.
Hands-on experience with a major cloud platform - Azure, AWS or GCP - with Azure preferred, including CI/CD, version control, automated testing and monitoring.
Working knowledge of AI security and governance concerns: prompt injection, data leakage, access control, PII and confidential data handling, auditability.
Technical credibility and leadership presence, with the ability to set direction, review others' work and drive execution without direct authority.
Strong communication skills, with the ability to explain technical tradeoffs to non-technical stakeholders.

Preferred Qualifications

Master's degree in Computer Science, Engineering or a related field.
Experience with Databricks, Delta Lake, Unity Catalog or comparable modern data platforms.
Experience with MLOps or LLMOps tooling and model lifecycle management.
Experience deploying AI capabilities in a regulated, confidentiality-sensitive or professional services environment.
Experience with fine-tuning, distillation or model customization and a clear view of when they are and are not warranted.
Experience with Infrastructure as Code and Governance as Code practices.

Other Skills And Abilities

Strong organizational and project management skills.
Strong attention to detail and commitment to quality.
Good judgment and sound decision-making under pressure.
Strong interpersonal and communication skills.
Able to work harmoniously and effectively with others across technical and business teams.
Able to preserve confidentiality and exercise discretion.
Able to manage multiple priorities and competing deadlines.

Attendance

This is a full-time position with a hybrid schedule. Regular, reliable attendance is expected and required. Additional hours may be required during periods of heavy workload, and flexibility in the daily work schedule is required to accommodate business requirements.

Applicants must be authorized to work in the United States without the need for employer sponsorship, now or in the future.