Forward Deployed Engineer & Agentic Workflow Engineer – AI Innovation & Transformation

United States Digital Space LLC; United States; Hybrid; USD 140,000 - 210,000; Full time

Benefits offered by this job

Healthcare

401(k) matching

Parental leave

Technology stipend

Wellness reimbursement

Job summary

United States Digital Space LLC is seeking a Forward Deployed Engineer to design, deploy, and manage production-grade agentic AI solutions for CFO and other enterprise functions. You will embed with client teams to build, test, and iterate agentic workflows delivering measurable value in compressed timelines.

You will work across software engineering, finance domain expertise, and client partnerships, writing production code and mentoring junior engineers in a fast-moving practice.

Qualifications

• 5+ years of software engineering with AI/LLM focus.
• Experience building multi-agent systems and tooling.
• Proficiency in Python and modern web stacks.

Responsibilities

• Deploy AI Jumpstart packages in client environments.
• Design multi-agent workflows and tool schemas.
• Develop LLM prompts, retrieval strategies, and secure outputs.
• Integrate ERP/CRM data via MCP connectors and APIs.
• Package agents as containerized services and monitor deployments.

Skills

Python

TypeScript/JavaScript

LangChain/LangGraph

Docker/Kubernetes

API integration

LLM & AI knowledge

Cloud platforms

Education

Bachelor's degree in CS or related field

Tools

FastAPI

LangChain

AutoGen

REST/GraphQL

Job description

From the beginning, our goal was to establish an advisory firm that stands apart from the rest – one that is grounded in our Core Values and dedicated to creating a positive experience not just for our clients, but for our people too. We firmly believe in the strength of collaboration, enthusiasm, generosity, and perseverance as the driving forces behind our success. With advisory solutions spanning accounting and risk, technology-enabled transformation, and transactions, we partner with our clients to solve today’s challenges and deliver present and future value.

Our commitment to our people has earned us numerous awards including Inc5000's Fastest Growing Companies and Glassdoor's Best Places to Work.

By joining our rapidly growing AI Innovation \& Transformation practice you will serve as a trusted partner to our clients. You’ll bring your first-hand engineering experience, unique perspectives, and functional knowledge to design, deploy, and manage production-grade agentic AI solutions for the Office of the CFO and other enterprise functions. As a Forward Deployed Engineer \& Agentic Workflow Engineer at the company you will be the tip of the spear for AI deployment at clients—embedding directly with client finance and operations teams to build, test, and iterate on agentic workflows that deliver measurable enterprise value on a compressed timeline. Operating at the intersection of software engineering, finance domain expertise, and client partnership, you will write production code alongside your clients, own the deployment of agentic solutions, and mentor junior engineers as a member of the practice team.

What you'll do:

• Rapid Jumpstart deployment: Deploy AI Jumpstart packages within client environments, configuring data connectors, calibrating agent logic, and validating outputs against source-system controls within the first week of engagement.
• Agentic workflow design \& build: Architect and implement multi-agent orchestration workflows using frameworks such as LangGraph, CrewAI, or AutoGen; design task decomposition, inter-agent messaging, tool-call schemas, and human-in-the-loop (HITL) / human-on-the-loop (HOTL) checkpoints appropriate to the risk and materiality of each workflow step.
• LLM integration \& prompt engineering: Write, version, and optimize system prompts and structured output schemas for LLM-powered agents; implement function-calling / tool-use patterns against financial APIs; and fine-tune retrieval strategies (hybrid structured + RAG) to maximize accuracy and auditability.
• Enterprise system integration: Build and certify MCP connectors and REST/GraphQL integrations to ERP (NetSuite, SAP, Oracle), EPM (Adaptive Planning, Anaplan), CRM (Salesforce), and HRIS (Workday) systems, ensuring data freshness, completeness, and reconciliation to source-system controls.

Production deployment \& reliability: Package agents as containerized microservices (Docker/Kubernetes or equivalent) and configure CI/CD pipelines, environment promotion (dev staging* production), and monitoring/alerting so agents run reliably at client scale.

• Client co-development: Work shoulder-to-shoulder with client finance, IT, and data teams; translate business requirements into technical agent design; facilitate working sessions; demonstrate working agents to executive stakeholders; and iterate rapidly based on feedback.
• SOX \& audit-readiness: Instrument agents with deterministic logging, source citations, and control documentation so every agent-generated output can be traced, validated, and presented to internal or external auditors.
• Contribute to developing and implementing firm-approved, AI-enabled solutions for clients, in accordance with company policies on data protection, intellectual property, and professional standards.
• Stay informed about emerging AI tools and techniques and collaborate with firm leadership to identify compliant opportunities to enhance client solutions and internal processes.

Practice Leadership: Serve as a key leader in the AI Innovation \& Transformation practice by:

• Developing reusable accelerators—contributing battle-tested code, workflow templates, and connector certifications back to the AI practice accelerator library to reduce deployment time on future engagements.
• Creating new delivery methodologies and service offerings that scale agentic solutions across clients and enterprise functions.
• Mentoring analysts and junior engineers on engagement teams, tracking and directing performance against objectives while encouraging continuous improvement and innovation.
• Contributing to recruiting, proposal writing, and firm-wide AI innovation initiatives.

What you'll bring:

• 5+ years of software engineering experience with at least 2 years focused on AI/LLM application development, agentic systems, or intelligent automation; prior “forward deployed” or client-embedded engineering experience strongly preferred.
• Hands-on production experience building multi-agent systems with LangChain/LangGraph, CrewAI, AutoGen, or equivalent frameworks; understanding of agent-loop design, task planning, tool-use, and memory management.
• Proficiency in Python (primary) and TypeScript/JavaScript; experience with FastAPI or equivalent for exposing agent capabilities as APIs.
• Deep understanding of LLM capabilities and limitations: prompt engineering, structured outputs, function calling, context-window management, cost optimization, and latency tradeoffs across frontier models.
• Experience integrating enterprise source systems via APIs and MCP connectors; familiarity with ERP, EPM, EDW/Data Lakes, and CRM data schemas in a finance context is a significant plus.
• Working knowledge of cloud data platforms (Azure, GCP, or AWS) and containerization (Docker, Kubernetes); experience with vector databases (Pinecone, Weaviate, or equivalent) and RAG pipelines.
• Finance domain fluency—ability to understand and implement workflows covering month-end close, variance analysis, revenue recognition, AR/AP, and FP\&A without requiring extensive hand-holding from client finance teams.
• Exceptional ability to operate in ambiguous, fast-moving client environments; a demonstrated track record of delivering working software in compressed, high-stakes timelines.
• Clear, confident communication with both technical and non-technical stakeholders; ability to present live-agent demonstrations to CFOs and finance leadership.
• Continuous Learning Mindset: Openness to continuously learning and applying emerging LLM capabilities, agent frameworks, and enterprise integration patterns.

Qualifications:

• A bachelor’s degree from an accredited university in computer science, software engineering, mathematics, or a related technical discipline.
• Relevant certifications in cloud platforms (Azure AI Engineer, AWS Machine Learning Specialty, GCP Professional ML Engineer), LangChain, or equivalent agentic AI tooling preferred.
• Willingness to travel domestically up to 20%–40% (varies by client engagement phase).
• Availability to work on client site or in office 3 days a week, with 2 days remote (hybrid environment).

Benefits Summary

The CrossCountry total rewards package includes comprehensive healthcare options, including medical, dental, and vision coverage; flexible spending accounts; and a 401(k) with company matching. Additionally, employees can take advantage of generous parental and maternity leave policies, technology stipends, and wellness reimbursement programs, all designed to support both professional growth and personal well-being.

Equal Employment Opportunity (EEO)

CrossCountry provides equal employment opportunities (EEO) to all employees and applicants for employment and believes that respect and fair treatment are critical to creating a productive and inclusive workplace. As an equal opportunity employer, CrossCountry is fully committed to comply with all federal, state, and local laws and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability, pregnancy, genetics, sexual orientation, veteran status, gender identity or expression or any other protected characteristic. The company also complies with pay transparency and labor laws applicable to all terms and conditions of employment.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.