Accellor

Principal Forward Deployment Engineer (FDE)

Accellor
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25 days ago
San Jose, CA, USAStaff+

Base Salary

$200k - $225k/yr

Responsibilities

  • Run technical discovery workshops with customer architects, data leaders, and AI teams.
  • Own deployment scoping, acceptance criteria, technical architecture, implementation, evaluation, production deployment, adoption, and handoff.
  • Design AI-agent architectures covering data sources, MCP configuration, semantic context, governance, orchestration, schemas, and actions.
  • Define governed access patterns using RBAC, OAuth 2.1, semantic scoping, and audit-trail requirements.
  • Lead and grow a team of Forward Deployed Engineers delivering production systems with frontier models.
  • Translate complex AI and data concepts into executive-ready proposals and defend trade-offs with CxO-level stakeholders.
  • Identify product and architectural gaps, author technical specifications, and partner with Product and Engineering on scalable solutions.
  • Build reusable reference architectures, deployment patterns, tools, playbooks, and MCP blueprints.
  • Partner with Product, Research, Sales, and GTM to turn fieldwork into roadmap priorities and platform improvements.
  • Set performance expectations, mentor engineers, provide actionable feedback, and define scalable field-team staffing models.

Requirements

  • 15+ years of engineering or technical delivery experience, including 2+ years managing high-performing FDEs or customer-facing engineers.
  • 7+ years as a Solutions Architect, Principal SE, Forward Deployed Engineer, or Technical Lead at a data platform, AI, or enterprise SaaS company.
  • Customer-facing experience with senior technical buyers and architecture review boards.
  • Experience building and shipping production AI applications and leading high-pressure projects from prototype to production.
  • Ability to write and review production-grade frontend and backend code using JavaScript or Python.
  • Experience with LLMs or generative models and understanding of their effect on product experience.
  • Strong AI/ML literacy, including LLM capabilities, agentic architectures, RAG patterns, and prompt engineering.
  • Experience designing multi-tenant architectures, security objectives, and governed AI-agent data access.
  • Hands-on enterprise data integration experience with SQL, ETL/CDC pipelines, API design, ODBC/JDBC, and multi-source connectivity.
  • Experience with Snowflake, Databricks, Salesforce, and cloud-native deployment patterns.
  • Experience mentoring junior engineers without requiring direct reporting relationships.
  • Preferred experience with MCP, LangChain, CrewAI, Copilot Studio, or a similar embedded customer-facing engineering role.

Benefits

  • Base salary of $200,000 to $225,000 plus additional revenue-linked performance incentives.
  • Hybrid work arrangement with flexible work schedules and opportunities to work from home.
  • Paid time off and holidays, flexible and discretionary time off, healthcare coverage, retirement plan, flexible spending and health savings accounts, and life and AD&D insurance.
  • Professional development through communication and stress-management programs, certifications, and technical and soft-skill training.
  • Opportunities to work on projects across high-tech, communications, media, healthcare, retail, and telecom industries.
  • Collaborative environment with diverse colleagues and opportunities to collaborate abroad in global centers.

Tech Stack

DatabricksJavaScriptPythonSnowflakeSQL

Categories

Forward Deployed
Accellor

About Accellor

201-500 employees
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