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About This Role
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Job Category
Sales
Job Details
About Salesforce
Salesforce is the \#1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.
Ready to level\-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce.
About Salesforce
Salesforce is the \#1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.
Ready to level\-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce.
Delivering customer success with Data \+ AI \+ CRM \+ Trust requires more than product expertise; it requires deep technical architecture leadership. The Data \& AI Technical Architect is a senior, hands\-on technical architect responsible for designing, validating, and operationalizing enterprise\-grade data and AI architectures centered on Salesforce D360 and the Agentforce platform.
This role sits at the intersection of data engineering, platform architecture, and applied AI. You will work directly with customer architects, data engineers, and platform owners to design scalable, secure, and performant solutions that integrate D360 into complex enterprise ecosystems—including hyperscalers, data lakes, real\-time pipelines, identity systems, and governance frameworks.
This role owns the technical architecture end\-to\-end: from deep discovery and system design, through hands\-on validation, to production readiness and long\-term scalability. Your work establishes the data foundation required for trusted AI, agentic workflows, and measurable business outcomes.
Your Impact
- Own and drive the full technical lifecycle, from deep technical discovery and system design to architecture validation and technical close, across in\-person and virtual engagements.
- Design and validate end\-to\-end data architectures integrating Salesforce D360 with enterprise systems (Snowflake, Databricks, BigQuery, Redshift, streaming platforms, MDM, and source systems).
- Own technical architecture decisions, including data modeling, identity resolution, real\-time vs. batch patterns, data graph design, and activation strategies within D360\.
- Partner with Account Executives to shape technical close strategy, grounded in architectural feasibility, scalability, and customer data realities.
- Execute hands\-on technical validation (POCs, architectural walkthroughs, reference implementations) to de\-risk complex deals and accelerate D360 adoption.
- Define repeatable industry\-specific reference architectures built on D360 that scale across accounts and drive consistent outcomes.
- Collaborate deeply with Salesforce Product \& Engineering teams to:
+ Influence roadmap through high\-signal Voice of the Customer feedback
+ Validate architectural patterns against upcoming D360 capabilities
- Act as a technical authority during escalations, architecture reviews, and executive\-level design discussions.
- Produce high\-fidelity technical assets (architecture diagrams, Demos, governance models, activation patterns) used by field teams, partners, and customers.
- Serve as a trusted technical advisor to customer Chief Data Officers, Enterprise Architects, and Platform Owners.
- Ensure D360 architectures align to security, privacy, compliance, and trust requirements—especially in regulated industries.
- Represent Salesforce’s technical point of view for modern data and AI architectures, with D360 as the system of activation, at customer briefings and technical forums.
Qualifications
You bring progressively senior technical responsibility, including:
- 7\+ years of hands\-on experience designing and delivering data, analytics, and AI architectures in enterprise environments.
- Strong background in data engineering, platform architecture, or technical architecture roles (pre\-sales or post\-sales).
- BS in Computer Science, Engineering, Data Science, or equivalent technical field (advanced degree preferred).
- Proven experience integrating complex, distributed data ecosystems with activation platforms like D360 to drive business outcomes.
- Deep expertise in:
+ Modern cloud data platforms (Snowflake, Databricks, BigQuery, Redshift)
+ Data ingestion patterns (batch, streaming, CDC)
+ Identity resolution, data modeling, and graph\-based relationships
- Hands\-on proficiency with Python/R, data frameworks (DataFrames, pandas), and analytics workflows (Jupyter).
- Strong technical fluency with Salesforce platform architecture, including D360 and core Salesforce services.
- Experience guiding architectural conversations with senior technical stakeholders and influencing platform and data strategy decisions.
- Ability to translate complex technical concepts into clear architectural guidance for both technical and executive audiences.
- Experience operating in large, matrixed organizations with complex stakeholder environments.
Technical Skill Set
As a senior technical architect, you bring depth across:
Data Architecture
- Cloud data platforms: Snowflake, Databricks, BigQuery, Redshift
- Data modeling, identity resolution, entity relationships, D360 data graph design
- Batch, real\-time, and hybrid ingestion patterns into D360
- Data quality, lineage, governance, and trust frameworks
AI \& Analytics
- Python/R, Jupyter, data wrangling, feature preparation
- Applied machine learning concepts and AI\-readiness architecture on top of D360
- Analytics and BI tools: Tableau, Looker, Power BI
Salesforce Platform
- Deep hands\-on knowledge of Salesforce architecture
- Salesforce Admin / Advanced Admin\-level proficiency
- Experience designing scalable, secure solutions using D360 as the activation layer across Salesforce Clouds
Unleash Your Potential
When you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance and *be your best* , and our AI agents accelerate your impact so you can *do your best* . Together, we’ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future — but to redefine what’s possible — for yourself, for AI, and the world.
Accommodations
If you need a reasonable accommodation during the application or the recruiting process, please submit a request via this Accommodations Request Form .
Please note that Salesforce uses artificial intelligence (AI) tools to help our recruiters assess and evaluate candidates’ resumes and qualifications throughout the recruiting process. Humans will always make any candidate selection and hiring decisions. Please see our Candidate Privacy Statement for more information about how we use your personal data and your rights, including with regard to use of AI tools and opt out options.
Posting Statement
Salesforce is an equal opportunity employer and maintains a policy of non\-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that’s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.
In the United States, compensation offered will be determined by factors such as location, job level, job\-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. Salesforce offers a variety of benefits to help you live well including: time off programs, medical, dental, vision, mental health support, paid parental leave, life and disability insurance, 401(k), and an employee stock purchasing program. More details about company benefits can be found at the following link: https://www.salesforcebenefits.com.
At Salesforce, we believe in equitable compensation practices that reflect the dynamic nature of labor markets across various regions.\&\#xa;\&\#xa;The typical base salary range for this position is $173,460 \- $231,980 annually\&\#xa;\&\#xa;There is a different range applicable to specific work locations. In California and New York, and select cities in the metropolitan areas of Boston, Chicago, Seattle, and Washington DC, the base pay range for this role in those locations is $190,750 \- $255,150 per year. Your recruiter can share more about the specific salary range for the job location during the hiring process.\&\#xa;\&\#xa;The range represents base salary only, and does not include company bonus, incentive for sales roles, equity or benefits, as applicable.
Salary Context
This $173K-$255K range is below the median for AI Architect roles in our dataset (median: $225K across 99 roles with salary data).
Role Details
About This Role
This role sits at the intersection of AI and engineering, building systems that bring machine learning capabilities into production environments. The scope varies by company, but the common thread is applying AI technology to solve real business problems at scale. Most AI roles today require a combination of software engineering fundamentals and domain-specific ML knowledge, with the exact mix depending on the team's maturity and the product they're building.
The AI job market is evolving fast. New role categories emerge as companies figure out what they need to ship AI-powered products. What matters most is the ability to learn quickly, build working systems, and iterate based on real-world performance data. The specific title matters less than the skills you bring and the problems you can solve. Companies are past the experimentation phase and want engineers who can deliver production-quality systems that work reliably at scale.
Across the 26,159 AI roles we're tracking, AI Architect positions make up 1% of the market. At Salesforce, this role fits into their broader AI and engineering organization.
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
What the Work Looks Like
Day-to-day work involves a mix of building, debugging, and collaborating. You'll write code, review pull requests, participate in design discussions, and work with cross-functional teams (product, design, data) to define what AI features should do and how they should behave. Expect to spend time on both technical implementation and communication. Most AI teams operate in two-week sprint cycles, with regular demos and retrospectives. The ratio of heads-down coding to meetings and reviews varies by seniority, with senior roles spending more time on architecture decisions and mentorship.
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
Skills Required
Python and cloud platform experience are common requirements. Specific skill needs vary by company and focus area, but familiarity with ML frameworks, data pipelines, and API design covers the basics for most roles. RAG (Retrieval-Augmented Generation), vector databases, and LLM API integration are increasingly standard requirements across role types.
Beyond the core stack, communication skills matter more than many technical candidates realize. The ability to explain AI capabilities and limitations to non-technical stakeholders is a differentiator at every level. Technical writing, documentation, and clear thinking about tradeoffs are underrated skills in AI roles. Experience with evaluation methodology (how to measure whether an AI system is working well) is becoming a core requirement, especially for roles that involve LLM integration.
Look for job postings that specify the problems you'll work on, the tech stack, and the team structure. Vague postings that list every AI buzzword are often a sign the company hasn't figured out what they need. Strong postings describe the product context, the team you'd join, and the specific challenges you'd tackle.
Compensation Benchmarks
AI Architect roles pay a median of $292,900 based on 108 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $131,300. This role's midpoint ($214K) sits 27% below the category median. Disclosed range: $173K to $255K.
Across all AI roles, the market median is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $76,880; Mid: $131,300; Senior: $227,400; Director: $244,288; VP: $234,620.
Salesforce AI Hiring
Salesforce has 19 open AI roles right now. They're hiring across AI/ML Engineer, AI Architect, AI Software Engineer. Positions span San Francisco, CA, US, New York, NY, US, Chicago, IL, US. Compensation range: $155K - $451K.
Location Context
AI roles in New York pay a median of $200,000 across 1,670 tracked positions. That's 9% above the national median.
Career Path
Common paths into AI Architect roles include Software Engineer, Data Scientist, Data Analyst.
From here, career progression typically leads toward Senior Engineer, AI Architect, Engineering Manager, Principal Engineer.
Focus on building things that work. A deployed project that solves a real problem is worth more than any certification. Contribute to open-source, build portfolio projects, and invest in fundamentals (software engineering, statistics, systems design) rather than chasing the latest framework. The AI field moves fast, but the engineers who succeed long-term are the ones with strong fundamentals who can adapt to new tools and paradigms as they emerge.
What to Expect in Interviews
AI interviews typically combine coding challenges (Python-focused), system design questions tailored to the role, and discussions about your experience with relevant tools and frameworks. Strong candidates demonstrate both technical depth and the ability to make pragmatic engineering tradeoffs. Prepare portfolio projects that demonstrate end-to-end capability rather than isolated skills.
When evaluating opportunities: Look for job postings that specify the problems you'll work on, the tech stack, and the team structure. Vague postings that list every AI buzzword are often a sign the company hasn't figured out what they need. Strong postings describe the product context, the team you'd join, and the specific challenges you'd tackle.
AI Hiring Overview
The AI job market has 26,159 open positions tracked in our dataset. By seniority: 2,416 entry-level, 16,247 mid-level, 5,153 senior, and 2,343 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (1,863 positions). The remaining 24,200 roles require on-site or hybrid attendance.
The market median for AI roles is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. Highest-paying categories: AI Engineering Manager ($293,500 median, 28 roles); AI Architect ($292,900 median, 108 roles); AI Safety ($274,200 median, 19 roles).
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
The AI Job Market Today
The AI job market spans 26,159 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (23,752), AI Software Engineer (598), AI Product Manager (594). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (2,416) are outnumbered by mid-level (16,247) and senior (5,153) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 2,343 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (1,863 positions), with 24,200 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $184,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $309,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $122,200. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Rag (16,749 postings), Aws (8,932 postings), Rust (7,660 postings), Python (3,815 postings), Azure (2,678 postings), Gcp (2,247 postings), Prompt Engineering (1,469 postings), Openai (1,269 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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