Data & AI Practice Leader (North America)

Accellor is an AI-native services firm focused on delivering measurable business outcomes through advanced AI, data, and engineering capabilities. We help global innovators and Fortune 100 enterprises modernize their architectures, scale operations, and operationalize intelligence across the enterprise.

Our core focus centers on transforming advanced AI from proofs-of-concept into production-grade systems. Spanning AI solutions, robust data services, enterprise applications, and product engineering — we tailor our offerings to the distinct operational needs of industries such as healthcare, life sciences, telecom, retail, financial services, and technology.

Operating as an extension of our clients' teams, we combine design thinking with technology-agnostic architectures to ensure faster time-to-value and seamless system interoperability. From initial strategy to full-scale deployment, we build intelligent, connected ecosystems that drive sustained enterprise value and redefine the future of transformation.

With a proven track record of enabling Fortune 100 enterprises and global innovators, Accellor stands as a trusted partner for organizations seeking to harness the full potential of AI. Our vision is clear: to build intelligent, connected ecosystems that deliver measurable outcomes and redefine the future of enterprise transformation.

About the role

As the AI Practice Lead and Principal FDE, you’ll be the senior technical leader inside our most strategic enterprise engagements. You'll embed with customers to translate AI ambitions into production architectures, designing how data, AI, and governance fit together end-to-end. You'll be the technical voice the customer trusts and the field-level expert whose patterns shape what we build next in product.

You'll lead FDEs through high-stakes, ambiguous customer deployments and own technical and business value outcomes end to end. You'll grow a team that can operate under pressure and help our organization learn from the field.

You'll partner closely with Delivery, Solutions, Sales, and GTM to ensure customer and industry specific solution development is prioritized to support accelerated growth. Your decisions will influence how we are trusted by the customers closest to our deployment work. This role works directly with strategic customers and designs how AI, data and governance come together end-to-end to ensure deployments are scalable, secure, and deliver measurable outcomes. You and your team will define architectures and best practices for AI deployment at scale.Your success will be measured by patterns that accelerate future deployments, strengthen technical credibility with enterprise buyers, and reduce time to value across engagements.

In this role you will:

• Run technical discovery workshops with customer architects, data leaders, and AI teams, mapping data sources, MCP Workspace scoping, and agent tooling requirements
• Own the scoping for AI deployments with clear acceptance criteria around agent accuracy, data coverage, and governance
• Translate complex AI + data concepts into executive-ready architecture proposals; defend trade-offs to CxO-level stakeholders
• Lead and grow a team of FDE delivering production systems with frontier models
• Own end-to-end delivery outcomes through clarity, speed, tight coordination, and technical quality
• Own the technical solution end to end, from customer discovery and workflow scoping through architecture, hands-on implementation, evaluation, production deployment, adoption, and handoff
• Partner credibly with customer engineers, operators, and domain experts to frame ambiguous problems, define scope, and translate business workflows into technical requirements and measurable outcomes.
• Design solutions across various AI sources covering MCP server configuration, semantic context modeling, and governance integration
• Architect agent orchestration, defining which data, schemas, and actions each agent can access in production
• Design governed access patterns for AI agents: RBAC, OAuth 2.1, semantic scoping, and audit-trail requirements
• Define AI Best practices using agents, skills and LLMs to drive successful customer outcomes
• Author technical specifications and implementation recommendations for solution enhancements, including both features and architectural improvements
• Build reusable reference architectures, deployment patterns, and MCP blueprints that reduce implementation friction and accelerate future customer deployments
• Codify what works into tools, playbooks, and roadmap inputs that create leverage for our enterprise customers
• Notice early indicators and raise them with urgency, whether in product behavior, customer environments, or delivery practices
• Use judgement to distinguish what requires action and what does not
• Set a high bar for FDE performance and support each person’s growth through direct, actionable feedback
• Define how we staff and support field teams that can scale without added complexity

You might thrive in this role if you:

• Bring 15+ years of engineering or technical delivery experience, including 2+ years managing high-performing FDE 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 track record with senior technical buyers and architecture review boards
• High agency; comfortable being the senior technical voice in the room with the customer
• Ability to translate complex AI + data concepts into executive-ready architecture proposals
• Has built and shipped production AI applications, not just prototypes
• Have led high-pressure technical projects from prototype to production
• Write and review production-grade code across frontend and backend using JavaScript or Python
• Have built or deployed systems powered by LLMs or generative models and understand how model behavior affects product experience
• Simplify complex work and make fast, sound decisions under pressure
• Elevate team performance through clarity, not process
• Operate with urgency in ambiguous or evolving environments
• Translate field experience into sharp, actionable feedback for Product and Research
• Build deep trust with your team by modeling calm, focus, and judgment when it matters most
• Strong AI/ML literacy: LLM capabilities, agentic architectures, RAG patterns, prompt engineering, and when to apply each
• Able to define Multi-tenant Architectural patterns and security objectives
• Hands-on enterprise data integration: SQL, ETL/CDC pipelines, API design, ODBC/JDBC, and multi-source connectivity
• Able to design governed data access for AI agents, RBAC, OAuth 2.1, semantic scoping, and audit-trail requirements
• Experience with modern data stacks (Snowflake, Databricks, Salesforce) and cloud-native deployment patterns
• Experience mentoring junior engineers without requiring direct reporting relationships
• This role requires you to work from our San Jose offices at least 3 days a week.

Nice to Have:

• Direct experience with the MCP protocol and AI agent frameworks (LangChain, CrewAI, Copilot Studio)
• Prior experience as an FDE or in a similar embedded customer-facing engineering role

Pay Transparency

At Accellor, we believe in equitable compensation. The base salary for this position is $225,000 to $275,000 with additional variable pay, equity and revenue linked performance incentives. The actual pay will depend on your skills, experience, and qualifications. The salary range is subject to change. Speak with your recruiter about any questions.

Benefits

We strive to offer benefits that support the diverse needs of our employees. Our package includes perks like flexible and discretionary time off, healthcare coverage for you and your loved ones, and a retirement savings plan to help you plan for the future. Additionally, we offer access to flexible spending and health savings accounts, life and AD&D insurance, and opportunities for professional development.

Accellor is proud to be an equal-opportunity employer. We do not discriminate in hiring or any employment decision based on race, color, religion, national origin, age, sex (including pregnancy, childbirth, or related medical conditions), marital status, ancestry, physical or mental disability, genetic information, veteran status, gender identity or expression, sexual orientation, or other applicable legally protected characteristics.