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Ai Practice Lead Jobs (NOW HIRING)

We are seeking a high-impact, business-driven AI Solution Principal to spearhead opportunity creation, client acquisition, and revenue generation in the AI space. This role is strictly focused on ...

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Marlabs, a global AI and Digital Solutions Consulting firm, delivers intelligent solutions across ... Data Practice Lead | About You As a Data Practice Lead, you are a strategic and hands-on expert in ...

Marlabs, a global AI and Digital Solutions Consulting firm, delivers intelligent solutions across ... Data Practice Lead | About You As a Data Practice Lead, you are a strategic and hands‑on expert ...

Marlabs, a global AI and Digital Solutions Consulting firm, delivers intelligent solutions across ... Data Practice Lead | About You As a Data Practice Lead, you are a strategic and hands‑on expert ...

Svitla Systems Inc. is seeking an AI Solutions/Practice Lead for a full-time position (40 hours per week) to own the solution strategy and sales process for AI-related engagements with enterprise ...

Rysun guides and accelerates the AI & Data strategy and Digital Transformation programs for Fortune ... We are seeking an experienced Data Practice Lead to design and implement scalable, enterprise-grade ...

Rysun guides and accelerates the AI & Data strategy and Digital Transformation programs for Fortune ... We are seeking an experienced Data Practice Lead to design and implement scalable, enterprise-grade ...

Rysun guides and accelerates the AI & Data strategy and Digital Transformation programs for Fortune ... We are seeking an experienced Data Practice Lead to design and implement scalable, enterprise-grade ...

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Ai Practice Lead information

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How much do ai practice lead jobs pay per hour?

As of Sep 13, 2026, the average hourly pay for ai practice lead in the United States is $22.20, according to ZipRecruiter salary data. Most workers in this role earn between $15.38 and $24.76 per hour, depending on experience, location, and employer.

What is an AI Practice Lead?

An AI Practice Lead is a senior professional responsible for guiding and managing an organization’s artificial intelligence (AI) initiatives. They oversee the development and implementation of AI strategies, lead technical teams, and ensure that AI projects align with business goals. AI Practice Leads also collaborate with stakeholders, provide thought leadership, and stay updated on emerging AI trends and technologies. Their role often includes mentoring team members and shaping the organization’s AI capabilities to drive innovation and competitive advantage.

What are the key skills and qualifications needed to thrive as an AI Practice Lead?

To thrive as an AI Practice Lead, you need deep expertise in artificial intelligence, machine learning, and data science, often supported by an advanced degree in computer science or a related field. Familiarity with AI platforms (such as TensorFlow, PyTorch), cloud services (like AWS, Azure, or Google Cloud), and certifications in AI/ML are typically required. Strong leadership, communication, and strategic thinking skills help drive cross-functional teams and client engagement. These abilities ensure the successful delivery of AI solutions that align with business objectives and foster innovation.

How does an AI Practice Lead typically collaborate with cross-functional teams to drive AI initiatives within an organization?

An AI Practice Lead often works closely with data scientists, engineers, product managers, and business stakeholders to ensure successful AI project delivery. They are responsible for translating business goals into AI solutions, guiding technical teams, and aligning project objectives across departments. Regular meetings and collaborative workshops are common, fostering a shared understanding of priorities and challenges. This role requires strong communication skills to bridge technical expertise with strategic business needs, ensuring impactful AI adoption across the organization.

What is the difference between Ai Practice Lead vs Data Scientist?

AspectAi Practice LeadData Scientist
Required CredentialsAdvanced degrees in AI, Machine Learning, or related fields; leadership experienceDegree in Computer Science, Statistics, or related fields; strong programming skills
Work EnvironmentLeads AI projects, collaborates with cross-functional teams, strategic planningAnalyzes data, develops models, interprets results, often in research or product teams
Employer & Industry UsageUsed in tech companies, consulting firms, AI-focused organizationsCommon in tech, finance, healthcare, and research institutions

The Ai Practice Lead typically oversees AI initiatives, requiring leadership and strategic skills, while Data Scientists focus on analyzing data and building models. Both roles often require similar technical credentials but differ in scope and responsibilities.

What cities are hiring for Ai Practice Lead jobs?

Cities with the most Ai Practice Lead job openings:

What states have the most Ai Practice Lead jobs?

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What are popular job titles related to Ai Practice Lead jobs?

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Infographic showing various Ai Practice Lead job openings in the United States as of June 2026, with employment types broken down into 88% Full Time, 10% Part Time, and 2% Contract. Highlights an 70% Physical, 3% Hybrid, and 27% Remote job distribution, with an average salary of $46,178 per year, or $22.2 per hour.

AI Practice Lead & Principal FDE

San Jose, CA • On-site

Accellor
IT Services • 201 - 500 employees

Full-time

Medical, Life, Retirement, PTO

Re-posted 10 hours ago


Job description

Accellor is an AI-native services firm purpose-built for the post-ChatGPT era. Free from legacy constraints, we focus on delivering measurable business outcomes through advanced AI, data, and engineering capabilities. Our mission is to operationalize AI at scale and unlock sustained enterprise value. 

Our offerings span AI solutions, data services, enterprise applications, and product engineering, tailored to industry-specific needs across healthcare, life sciences, telecom, retail, financial services, and technology. By leveraging design thinking and technology-agnostic architectures, we ensure faster time-to-value and seamless interoperability. 

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
  • Identify architectural and product gaps during live enterprise engagements and partner with Product and Engineering to define scalable solutions
  • Author technical specifications and implementation recommendations for enhancements, including both features and core architectural improvements
  • Build reusable reference architectures, deployment patterns, and MCP blueprints that reduce implementation friction and accelerate future customer deployments
  • Translate recurring customer deployment challenges into scalable platform capabilities and architectural standards
  • 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

Requirements

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
  • Worked on a SaaS Platform in an Architect Profile (or closely aligned role)
  • 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

Benefits

At Accellor, we believe in equitable compensation. The base salary for this position will be in the range of $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.  

In addition, we offer: 

Work-Life Balance: Accellor prioritizes work-life balance, which is why we offer, flexible work schedules, opportunities to work from home, and paid time off and holidays.  

Financial and Medical Benefits: Our package includes perks like flexible and discretionary time off, healthcare coverage for you and your loved ones, and a retirement plan to help you plan for the future. Additionally, we offer access to flexible spending and health savings accounts, life and AD&D insurances. 

Professional Development: Our dedicated Learning & Development team regularly organizes Communication skills training, Stress Management program, professional certifications, and technical and soft skill trainings. 

Exciting Projects: We focus on industries like High-Tech, communication, media, healthcare, retail and telecom. Our customer list is full of fantastic global brands and leaders who love what we build for them. 

Collaborative Environment: You can expand your skills by collaborating with a diverse team of highly talented people in an open, laidback environment - or even abroad in one of our global centres. 

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