CrossCountry Consulting
CrossCountry Consulting2 open roles

Forward Deployed Engineer, Agentic Workflows

$150–285kUnited States (Remote)RemoteSeniorFull-time

Posted Sep 28, 2026

The role in short

Embed with client finance teams to design, build, and deploy production-grade agentic AI workflows and integrations.

CrossCountry Consulting is the transformation partner for the Office of the CFO. As a trusted advisor to Fortune 500 companies, emerging growth market leaders, and private equity sponsors, we combine deep domain expertise with the power of data, AI, and technology to modernize workflows, drive human-centered change, and maximize transaction value. Grounded in our Core Values, we are committed to solving today's most complex challenges while delivering a better experience for our clients, our people, and our communities. When you join CrossCountry, you become part of a team that believes in collaboration, generosity, and the drive to help our clients work smarter, build resiliency, and prepare for the future.

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 CrossCountry Consulting 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:

Client Delivery

Lead the development and delivery of services in the following areas:

  • 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:

  • 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.
  • Remote environment - Willingness to travel domestically up to 20%–40% (varies by client engagement phase).
  • Hybrid Environment - Availability to work on client site or in office 3 days a week, with 2 days remote

#LI-Remote

#LI-NB1

In accordance with applicable pay transparency laws, CrossCountry Consulting provides the following estimated compensation for this role. This position may be filled at either the Manager or Associate Director level. Level and final compensation will be determined based on a range of factors, including but not limited to skills, experience, education, licenses, certifications, business needs, internal equity, and work location.

Estimated base salary range:

  • Most U.S. locations: $150,000 – $250,000 per year
  • New York City and San Francisco metro areas: $175,000 – $285,000 per year

This role is also eligible for an annual bonus. CrossCountry Consulting offers a comprehensive benefits package, including [medical, dental, and vision coverage; 401(k) with company match; paid time off; and parental leave].

Applications will be accepted through December 31, 2026.

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. For detailed information about benefits at CrossCountry, please visit our dedicated benefits site: https://www.crosscountry-consulting.com/careers/benefits/.

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.

Prep for this interview

5 questions likely to come up at CrossCountry Consulting, each matched to a line in this posting.

  1. 1Cloud, deployment and security
    They wrote: “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.”

    How would you debug a deployment that works in staging but fails at the customer's site?

    How to answer

    Why they ask: Customer environments differ in ways you can't see. This tests method under pressure.

    1. Compare versions, config and environment variables
    2. Check network rules, proxies and certificates (common in enterprise)
    3. Look at resource limits and permissions
    4. Add the missing check to your install steps afterwards

    Tip: List the usual suspects and how you'd check each without full access.

  2. 2LLMs, RAG and agents
    They wrote: “Deep understanding of LLM capabilities and limitations: prompt engineering, structured outputs, function calling, context-window management, cost optimization, and latency tradeoffs across frontier models.”

    When would you fine-tune a model, and when is prompting or retrieval enough?

    How to answer

    Why they ask: Customers often ask for fine-tuning first. They want to hear you pick the cheapest thing that works.

    1. Try clear prompts and examples first; measure against a test set
    2. If the model lacks the customer's facts, add retrieval
    3. Fine-tune when you need a format or behaviour prompts can't hold, and you have good examples
    4. Count the cost: training data, upkeep and re-testing on every model update

    Tip: Start from what's wrong: missing knowledge points to retrieval, wrong style or format points to fine-tuning.

  3. 3Discovery and scoping
    They wrote: “Clear, confident communication with both technical and non-technical stakeholders; ability to present live-agent demonstrations to CFOs and finance leadership.”

    A senior executive and the hands-on team want different things. How do you handle it?

    How to answer

    Why they ask: Enterprise deployments have several stakeholders. Senior FDEs are expected to align them, not pick a side quietly.

    1. Meet each side to learn what they need and why
    2. Find the shared goal (usually the business metric the executive owns)
    3. Propose a plan that meets that goal and removes the team's biggest pain
    4. Get a written decision so the project doesn't stall later

    Tip: Show that you get both views on the table early and tie the plan to the goal the executive owns.

  4. 4Integrations and APIs
    They wrote: “Proficiency in Python (primary) and TypeScript/JavaScript; experience with FastAPI or equivalent for exposing agent capabilities as APIs.”

    Walk me through connecting our product to a customer's internal system that has no documentation.

    How to answer

    Why they ask: This happens weekly in the job. They want a calm, step-by-step method.

    1. Find who owns the system and get read access to a test environment
    2. Watch real traffic or logs to learn the data shapes
    3. Build a thin adapter with logging around every call
    4. Agree on how failures get reported, and who fixes what

    Tip: Talk about finding the owner of the system first. The code is the easy part.

  5. 5Ownership and working with customers
    They wrote: “Exceptional ability to operate in ambiguous, fast-moving client environments; a demonstrated track record of delivering working software in compressed, high-stakes timelines.”

    Tell me about a project where the requirements kept changing. What did you do?

    How to answer

    Why they ask: Ambiguity is the norm. They want proof you can keep moving without a clear spec.

    1. The project and why requirements kept moving
    2. What you did to pin them down (short demos, written decisions)
    3. The trade-offs you made to keep shipping
    4. The result, with a number if you have one

    Tip: Show how you reduced the change, beyond how you coped with it.

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CrossCountry Consulting

$150–285k · Remote

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