Principal Forward Deployment Engineer

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☕ Washington – Remote

☕ Washington – Remote

💵 $200k - $225k / year

⏰ Full Time

🔴 Lead

⛑ DevOps & Site Reliability Engineer (SRE)

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Accellor

WebsiteLinkedInAll Job Openings

201 - 500 employees

💼 Consulting

🏥 Healthcare

🏨 Hospitality

Consulting • Healthcare • Hospitality

Accellor is a company offering AI-driven solutions across various industries, focusing on enhancing efficiency and engagement through advanced applications and data strategies. Their services include leveraging artificial intelligence for enterprise applications, product engineering, and cloud services to transform industries such as healthcare, manufacturing, financial services, real estate, retail, travel, and hospitality. Accellor partners with technology leaders like Salesforce and Microsoft Dynamics 365 to deliver personalized, intelligent business applications. Committed to responsible AI practices, Accellor helps organizations harness the potential of data and AI to drive strategic decisions, automate operations, and provide superior experiences.

📋 Description

• Run technical discovery workshops with customer architects, data leaders, and AI teams • Map data sources, MCP Workspace scope, and agent tooling requirements • Own scoping for AI deployments with acceptance criteria for agent accuracy, data coverage, and governance • Translate AI and data concepts into executive-ready architecture proposals and defend trade-offs to CxO stakeholders • Lead and grow a team of FDEs delivering production systems with frontier models • Own end-to-end technical and business value outcomes from discovery through deployment, adoption, and handoff • Partner with customer engineers, operators, and domain experts to define scope, technical requirements, and measurable outcomes • Design solutions involving MCP server configuration, semantic context modeling, and governance integration • Architect agent orchestration and define production data, schema, and action access • Design governed AI-agent access patterns using RBAC, OAuth 2.1, semantic scoping, and audit trails • Define AI best practices using agents, skills, and LLMs • Identify architectural and product gaps during enterprise engagements and partner with Product and Engineering on scalable solutions • Author technical specifications and implementation recommendations • Build reusable reference architectures, deployment patterns, and MCP blueprints • Translate recurring deployment challenges into platform capabilities and architectural standards • Codify effective practices into tools, playbooks, and roadmap inputs • Raise urgent issues in product behavior, customer environments, and delivery practices • Set FDE performance standards and support team growth through direct feedback • Define staffing and support models for scalable field teams

🎯 Requirements

• 15+ years of engineering or technical delivery experience • 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 • Ability to translate complex AI and data concepts into executive-ready architecture proposals • Experience building and shipping production AI applications, not just prototypes • Experience working on a SaaS platform in an architect profile or closely aligned role • Experience leading high-pressure technical projects from prototype to production • Ability to write and review production-grade frontend and backend code using JavaScript or Python • Experience building or deploying systems powered by LLMs or generative models • Strong AI/ML literacy, including LLM capabilities, agentic architectures, RAG patterns, and prompt engineering • Ability to define multi-tenant architectural patterns and security objectives • Hands-on enterprise data integration experience with SQL, ETL/CDC pipelines, API design, ODBC/JDBC, and multi-source connectivity • Ability to design governed AI-agent data access using RBAC, OAuth 2.1, semantic scoping, and audit trails • Experience with modern data stacks including Snowflake, Databricks, and Salesforce • Experience with cloud-native deployment patterns • Experience mentoring junior engineers without direct reporting relationships • Nice to have: direct MCP protocol and AI agent framework experience with LangChain, CrewAI, or Copilot Studio • Nice to have: prior FDE or similar embedded customer-facing engineering experience

🏖️ Benefits

• Base salary of $200,000 to $225,000 • Additional revenue-linked performance incentives • Flexible work schedules • Opportunities to work from home • Paid time off and holidays • Flexible and discretionary time off • Healthcare coverage for you and your loved ones • Retirement plan • Flexible spending accounts • Health savings accounts • Life and AD&D insurance • Communication skills training • Stress Management program • Professional certifications • Technical and soft skill trainings • Opportunities to collaborate with a diverse team in an open, laidback environment • Opportunity to work abroad in one of Accellor’s global centres