Solutions Builder - Private Equity
AI in this role
Architect and deploy production-grade agentic AI systems and multi-agent workflows directly for enterprise customers.
To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts.
Job Category
SalesJob 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 the RoleYou are the builder. Production delivery is your job. The pod exists to go fast and go deep.
Salesforce is hiring Solution Builders — senior individual contributors who are the technical engine of a 2-person delivery pod. You partner with a Director who owns strategy and customer relationships; you own the build. You design and deploy production-grade agentic AI systems directly at customer sites, working hands-on every day. No overhead, no managing other builders — just you, your pod partner, and the work in front of you.
This is a hands-on IC delivery role. Your output is working software in production at the customer.
What You'll Do
Build & Deploy (Primary Focus)
Architect, build, and deploy production-grade Agentforce and agentic AI solutions end-to-end — this is your core job
Design and implement AI agents, multi-agent orchestration, agentic workflows, and the integration patterns that hold up in enterprise environments
Own data pipelines, system integrations, and production AI infrastructure across Salesforce, Snowflake, Databricks, and customer platforms
Build rapidly from ambiguous requirements — prototype to validate, then engineer to last
Resolve complex technical blockers: data integration failures, orchestration breakdowns, model deployment issues
Drive solutions from first commit through production handoff and active customer consumption
Pod Partnership with Director
Operate as the technical execution half of a 2-person pod — the Director shapes what gets built and why; you own how it gets built and make sure it ships
Translate strategy and customer context from the Director into concrete technical decisions and daily delivery progress
Communicate blockers, risks, and architecture tradeoffs clearly and early so the pod stays in sync
Represent technical depth in customer-facing sessions — architecture reviews, demos, working sessions, production readouts
Flag patterns, gaps, and opportunities you see in the field back to the Director and to Agentforce product teams
Customer Engagement
Embed directly with customer engineering and data teams — not remotely, not occasionally, but as a consistent presence
Build trust with customer technical counterparts through delivery quality and technical credibility, not just relationship management
Guide customer teams through the technical decisions required to operationalize AI at scale
Surface expansion signals and customer feedback to the Director
Contribute reusable patterns, reference implementations, and field insights back to the broader Builder org
Craft & Continuous Growth
Stay sharp on Agentforce platform evolution, agentic delivery patterns, LLM advances, and the competitive AI landscape
Codify what you learn — reusable components, playbooks, and lessons from the field that raise the bar for the whole org
Bring a growth mindset to hard problems: when something breaks or doesn't work, you dig in rather than escalate
What You Bring
Required
4–8+ years of software engineering, AI delivery, or technical consulting, with hands-on ownership of production systems (Builder: 4–6 years; Senior Builder: 6–8+ years)
Proven track record building and shipping production software — not prototypes, not demos, but systems that run in the real world
Hands-on LLM integration experience: agent frameworks (LangChain, LlamaIndex, or equivalent), prompt engineering, and responsible AI practices in production
Fluency in Python, JavaScript/TypeScript, Java, or Apex — and the range to add to that list as the work demands
Deep experience in data modeling, APIs, and integration patterns — able to design them, not just consume them
Ability to work autonomously in ambiguous, fast-moving customer environments with real delivery accountability
Strong enough communication skills to engage technical stakeholders and explain architecture decisions clearly
Ability to operate effectively as the sole builder in a small, high-trust pod
Willingness to travel ~25% of the time, working directly at customer sites
Preferred
Salesforce platform expertise: Agentforce, Apex, LWC, Data Cloud, Salesforce APIs
Salesforce certifications (Platform Developer I/II, Agentforce Specialist, System Architect)
Experience with cloud data platforms (Snowflake, Databricks, BigQuery)
Prior experience in forward-deployed engineering, consulting, or professional services
Familiarity with DevOps/CI-CD, observability tooling, or data governance frameworks
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.Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records.At Salesforce, we believe in equitable compensation practices that reflect the dynamic nature of labor markets across various regions. The typical base salary range for this position is $88,970 - $287,910 annually 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 $97,960 - $316,750 per year. Your recruiter can share more about the specific salary range for the job location during the hiring process. The range represents base salary only, and does not include company bonus, incentive for sales roles, equity or benefits, as applicable.How we rate this
Solutions Builder - Private Equity at Salesforce rates 75 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- How do you structure and test a prompt to get consistent output from a language model?
- How have you integrated a large language model into a production application?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- How do you think about the risk of an AI system in this kind of role failing silently?
- Tell me about a project where agentic workflows was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Prompt Engineering, LLM Integration, AI Agents, AI Safety, and Agentic Workflows. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.
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