Forward Development Engineer

crosscountry-consulting; United States; Remote; USD 140,000 - 210,000; Full time

Benefits offered by this job

Healthcare coverage

401(k) matching

Parental leave

Tech stipend

Wellness reimbursement

Remote-first option

Job summary

crosscountry-consulting is seeking a seasoned engineer to design, build, and deploy production-grade agentic AI solutions inside client organizations, focusing on measurable enterprise value for finance and operations teams.

Embedded with client finance leadership, you will lead technical efforts, mentor junior engineers, and deliver integrated AI solutions across ERP, CRM, and HRIS systems while maintaining robust data controls and a strong client partnership.

Qualifications

• Bachelor's degree in computer science, software engineering, mathematics, or a related technical discipline from an accredited university.
• Hands-on engineering experience deploying AI or agentic solutions in production, including containerization with Docker and Kubernetes, vector databases such as Pinecone or Weaviate, and RAG pipelines.
• Finance domain fluency covering month-end close, variance analysis, revenue recognition, AR/AP, and FP&A workflows, with the ability to operate without extensive hand-holding from client finance teams.
• Demonstrated success delivering working software under compressed, high-stakes timelines in ambiguous client environments.
• Clear, confident communication with both technical and non-technical stakeholders.
• Continuous-learning mindset with openness to adopting emerging LLM capabilities, agent frameworks, and enterprise integration patterns.

Responsibilities

• Architect and implement multi-agent orchestration workflows using frameworks such as LangGraph, CrewAI, or AutoGen, including task decomposition, inter-agent messaging, tool-call schemas, and human-in-the-loop checkpoints calibrated to workflow risk.
• Deploy AI Jumpstart packages within client environments, configuring data connectors, calibrating agent logic, and validating outputs against source-system controls during the first week of engagement.
• Write, version, and optimize system prompts and structured output schemas for LLM-powered agents, implementing function-calling patterns against financial APIs and tuning retrieval strategies that combine structured queries with RAG.
• Build and certify integrations to enterprise systems including ERP (NetSuite, SAP, Oracle), EPM (Adaptive Planning, Anaplan), CRM (Salesforce), and HRIS (Workday), ensuring data freshness and reconciliation to source-system controls.
• Package and operate agents for production deployment, monitoring reliability and end-to-end performance.
• Mentor junior engineers on the practice team and present live-agent demonstrations to CFOs and finance leadership.

Skills

AI systems

Cloud architecture

Stakeholder communication

Mentoring

Education

Bachelor's degree in CS or related

Tools

Docker

Kubernetes

Vector databases (Pinecone/Weaviate)

RAG pipelines

Job description

Role overview

This role places a seasoned engineer directly inside client organizations to design, build, and deploy production-grade agentic AI solutions for finance and operations teams. The position sits at the intersection of software engineering, financial domain expertise, and client partnership, with a focus on delivering measurable enterprise value on compressed timelines. The engineer will be embedded with client finance leadership, including the Office of the CFO, and serve as a senior technical lead within an AI-focused transformation practice.

Responsibilities

• Architect and implement multi-agent orchestration workflows using frameworks such as LangGraph, CrewAI, or AutoGen, including task decomposition, inter-agent messaging, tool-call schemas, and human-in-the-loop checkpoints calibrated to workflow risk.
• Deploy AI Jumpstart packages within client environments, configuring data connectors, calibrating agent logic, and validating outputs against source-system controls during the first week of engagement.
• Write, version, and optimize system prompts and structured output schemas for LLM-powered agents, implementing function-calling patterns against financial APIs and tuning retrieval strategies that combine structured queries with RAG.
• Build and certify integrations to enterprise systems including ERP (NetSuite, SAP, Oracle), EPM (Adaptive Planning, Anaplan), CRM (Salesforce), and HRIS (Workday), ensuring data freshness and reconciliation to source-system controls.
• Package and operate agents for production deployment, monitoring reliability and end-to-end performance.
• Mentor junior engineers on the practice team and present live-agent demonstrations to CFOs and finance leadership.

Requirements

• Bachelor's degree in computer science, software engineering, mathematics, or a related technical discipline from an accredited university.
• Hands-on engineering experience deploying AI or agentic solutions in production, including containerization with Docker and Kubernetes, vector databases such as Pinecone or Weaviate, and RAG pipelines.
• Finance domain fluency covering month-end close, variance analysis, revenue recognition, AR/AP, and FP&A workflows, with the ability to operate without extensive hand-holding from client finance teams.
• Demonstrated success delivering working software under compressed, high-stakes timelines in ambiguous client environments.
• Clear, confident communication with both technical and non-technical stakeholders.
• Continuous-learning mindset with openness to adopting emerging LLM capabilities, agent frameworks, and enterprise integration patterns.

Nice to have

• Relevant certifications in cloud platforms (Azure AI Engineer, AWS Machine Learning Specialty, GCP Professional ML Engineer), LangChain, or equivalent agentic AI tooling.

Benefits and work setup

• Comprehensive healthcare coverage including medical, dental, and vision, plus flexible spending accounts and a 401(k) with company matching.
• Generous parental and maternity leave policies, technology stipends, and wellness reimbursement programs supporting professional growth and personal well-being.
• Remote-first option available with willingness to travel domestically up to 20–40 percent depending on engagement phase; hybrid option requires availability on client site or in office three days per week with two days remote.