LOADING
Location: Metro DC; Atlanta, GA; Raleigh, NC; Burlington, VT; or Remote/Hybrid
Type: Full-time
Salary: $130,000 – $185,000
Team: Business Automation (AI-Centric Solutions)
Reports to: Chief Innovation Officer
Travel: 0–10% (occasional client workshops and internal collaboration)
Johnson Lambert is a public accounting firm focused on audit, tax, and advisory services for the insurance and nonprofit sectors, as well as employee benefit plans. For more than three decades, we've combined deep domain expertise with a people-first culture built on agility, respect, and trust.
We're investing heavily in technology to transform how assurance and tax services are delivered—so our teams can spend more time on high-value judgment and our clients can benefit from faster, more insightful outcomes.
You'll join our Business Automation team, which is chartered with building the next generation of tools that power how we work—data, automation, and AI/agentic systems.
This is our first AI engineering hire and a truly greenfield role: no legacy codebase, no pre-baked platform. You will:
We are deeply invested in AWS and use multiple model providers (primarily AWS Bedrock, but also OpenAI, Gemini, Grok, and others). We expect you to select and combine the right tools for each use case—balancing risk, cost, performance, and long-term maintainability.
You'll also be the technical owner of key AI vendor relationships, working with partners who have helped us deliver proofs of concept and turning promising experiments into robust, in-house capabilities.
Define the reference architecture for LLM and agentic workloads (orchestration, retrieval, tools, evaluation, guardrails) on AWS.
Leverage services like Bedrock alongside external providers (OpenAI, Gemini, Grok, etc.) in a modular, provider-agnostic way.
Deliver copilots and agents that help our people draft workpapers, analyze documents, summarize findings, generate testing selections, and prepare client deliverables.
Work end-to-end: discovery with domain experts, prototyping, productionization, monitoring, and iteration based on feedback.
Design retrieval pipelines over internal content, structured data, and workpapers with appropriate metadata and access controls.
Implement agents that can call tools (internal APIs, calculators, automations, workflows) and operate within well-defined boundaries.
Partner with risk, security, and data teams to ensure responsible use of client data (PII handling, redaction strategies, no-train boundaries, access controls).
Establish patterns for prompt hardening, guardrails, and evaluation that reflect our professional standards obligations.
Serve as the hands-on technical counterpart for AWS, OpenAI, Google, xAI, and other partners.
Evaluate new capabilities, run proof-of-concepts, and decide when to build vs. buy vs. extend vendor solutions.
Work closely with our Data Engineer and automation leads to connect AI systems to clean, governed data and existing workflows.
Translate ambiguous business problems into concrete AI/engineering deliverables and roadmaps.
Set best practices for AI application development (testing, observability, CI/CD, experiment tracking, documentation).
Help hire, onboard, and mentor junior and mid-level engineers as the AI function grows.