AI Engineer

Pinnacle Financial Partners; Atlanta (GA); On-site; USD 140,000 - 190,000; Full time

Job summary

Pinnacle Financial Partners seeks an experienced MCP/AI Governance Engineer to design, build, and secure internal infrastructure that connects to AI agents and tools. You will work with engineering, security, legal/compliance, and AI product teams to ensure governance, auditable controls, and compliant integration across systems.

The role emphasizes designing secure MCP servers, gateways, and policy-driven controls, with a focus on least-privilege access, risk management, and scalable playbooks.

Qualifications

• 5+ years of software, platform, or security engineering experience.
• Strong proficiency in Python and R.
• Hands-on experience developing AI agents and agentic workflows, including tool-calling loops and orchestration.
• Familiarity with Claude Agent SDK, LangGraph, or similar; understanding agent failures in production.
• Build governance controls and MCP-related tooling; knowledge of authentication/authorization (OAuth 2.x) and cloud platforms.

Responsibilities

• Design, build, and maintain MCP servers exposing internal tools and data to AI agents.
• Operate an MCP gateway/registry with discovery, versioning, and deprecation.
• Implement authentication and authorization for MCP connections (OAuth 2.x, SSO, RBAC/ABAC).
• Define standards and SDK wrappers to enable teams to ship MCP servers quickly.
• Review third-party MCP servers for internal use; ensure governance and auditability.

Skills

5+ years exp

Python

R

Agentic workflows

OAuth/OIDC

AWS

Azure

CI/CD

Knowledge Graphs

Tools

Claude Agent SDK

LangGraph

MCP tooling

Job description

At Pinnacle, our goal is to create an atmosphere where people can become fully engaged, enjoy what they're doing and be successful. We work to ensure that every associate embraces what makes Pinnacle different and excellent. For us, it starts with hiring the right people.

• We hire like-minded people who share our values of Integrity, Fairness, Learning, Results, Partnership, Balance and Discipline.
• We hire experienced professionals who understand the industry and provide effective advice.
• We hire candidates who demonstrate a passion for client service. People who understand that distinctive service is more than smiling and being friendly – it’s about creating a client experience that is unmatched.
• But attracting the right people is only half the battle. We must ensure that every associate understands their actions affect the outcomes of the firm. Our Position Descriptions are not designed to list every aspect of a position but to serve as a general overview.

SUMMARY OF POSITION

We're rolling out AI assistants and agents across the business, and much of their power comes from connecting to internal systems through the Model Context Protocol (MCP). As our MCP and AI Governance Engineer, you'll build the infrastructure that lets teams do this safely: secure, well-governed MCP servers and gateways, plus the policies, controls, and monitoring that keep AI use auditable and compliant.

You’ll work with engineering, security, legal/compliance, and the teams building AI products while adhering to strict governance design.

PRIMARY RESPONSIBILITIES

• Design, build, and maintain MCP servers that expose internal tools, APIs, and data sources to AI agents
• Build and operate an MCP gateway or registry, including server discovery, versioning, approval workflows, and deprecation
• Implement authentication and authorization for MCP connections (OAuth 2.x, SSO integration, scoped tokens, least‑privilege access)
• Define standards, templates, and SDK wrappers so other teams can ship MCP servers quickly and consistently
• Review third‑party and community MCP servers before they’re approved for internal use

AI standards and controls

• Translate AI policy and regulatory requirements (e.g., EU AI Act, NIST AI RMF, ISO/IEC 42001, SOC 2, GDPR) into enforceable technical controls
• Implement policy‑as‑code for tool access, data classification, human‑in‑the‑loop approvals, and rate and scope limits on agent actions
• Build audit logging and traceability for agent activity: which model, which tool, which data, on whose behalf
• Maintain an inventory of AI systems, agents, models, and tool integrations, with risk tiering and ownership
• Support AI risk assessments, model and vendor reviews, and internal audits

Security and risk

• Threat‑model agentic systems and mitigate prompt injection, tool poisoning, confused‑deputy problems, data exfiltration, and excessive agency
• Implement guardrails such as input/output filtering, sandboxing, secrets mgmt., and egress controls
• Partner with the security team on detection, incident response, and red‑teaming for AI systems
• Monitor for anomalous agent behavior and build dashboards and alerts

Enablement

• Write clear documentation, reference architectures, and secure‑by‑default patterns
• Advise product and engineering teams on safe agent design
• Communicate governance requirements to technical and non‑technical stakeholders

ESSENTIAL QUALIFICATIONS & SKILLS

• 5+ years of software, platform, or security engineering experience
• Strong proficiency in Python and R, with experience building production APIs or services
• Hands‑on experience developing AI agents and agentic workflows, including designing tool‑calling loops, multi‑step planning and orchestration, memory and context mgmt., and human‑in‑the‑loop controls.
• Familiarity with frameworks such as the Claude Agent SDK, LangGraph, or similar, and an understanding of how agents fail in production.
• Build governance controls that work in practice.
• Hands‑on experience with MCP or comparable tool‑calling and agent integration frameworks
• Solid understanding of authentication and authorization (OAuth 2.x, OIDC, RBAC/ABAC, secrets management)
• Working knowledge of LLM application risks (prompt injection, data leakage, insecure tool use)
• Experience with cloud platforms (AWS, Azure), containers, and Continuous Integration/Delivery
• Ability to turn ambiguous policy requirements into concrete, testable engineering controls
• Clear written and verbal communication
• Experience creating Knowledge Graphs for AI

PREFERRED QUALIFICATIONS & SKILLS

• Experience with policy engines (OPA/Rego, Cedar) or API gateway tooling
• Background in application security, IAM, GRC engineering, or data governance
• Familiarity with AI governance frameworks (NIST AI RMF, ISO 42001, EU AI Act) or compliance programs (SOC 2, ISO 27001, HIPAA)
• Experience with observability tooling for AI or agent workloads
• Experience running AI red‑team exercises or security reviews
• Relevant certifications (CISSP, CCSP, AIGP, or similar)
• Contributions to open‑source MCP servers or related standards
• RAG, Entity Resolution & Deduplication, and Schema Design

Pinnacle provides equal employment opportunities to all associates and applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran’s status, genetic information, or any other status protected by federal, state or local law or ordinance.