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principal ai engineer

Ontrac Solutions

<div><h1 class="jobSectionHeader">Overview</h1>
We are seeking a Principal GenAI Architect / Forward Deployed Principal Engineer to lead the design, delivery, and productionization of enterprise-grade Generative AI solutions within a highly regulated banking environment. This role will partner directly with business, product, engineering, architecture, risk, cyber, legal, compliance, and model governance teams to translate high-impact financial services use cases into scalable, secure, and compliant AI systems.
The ideal candidate has deep experience designing and delivering production-scale GenAI solutions across enterprise environments, with strong exposure to banking, financial services, risk management, customer operations, regulatory controls, and data protection requirements. This person will serve as a recognized GenAI expert across the organization, helping define reusable patterns, influence platform roadmaps, and raise the technical bar for responsible AI adoption across lines of business.
<h2 class="jobSectionHeader">Key Responsibilities</h2>
<h3 class="jobSectionHeader">GenAI Architecture &amp; Production Readiness</h3>
Own and define enterprise-grade GenAI architectures for banking and financial services use cases, including RAG pipelines, agentic workflows, prompt orchestration, and multi-model routing strategies.
Drive production readiness for GenAI solutions, ensuring scalability, resiliency, observability, latency optimization, security, and cost efficiency.
Lead complex architectural decisions across data ingestion, vector databases, model selection, guardrails, API scalability, performance optimization, and secure integration with banking systems.
Establish reference architectures, reusable patterns, and best practices to accelerate responsible GenAI adoption across lines of business.
Partner with central AI platform teams to align solution architecture with enterprise AI services, platform capabilities, banking technology standards, and long-term roadmap priorities.
<h3 class="jobSectionHeader">Banking Use-Case Delivery</h3>
Act as a Forward Deployed Principal Engineer, partnering directly with business, product, and engineering teams to deliver high-impact GenAI use cases from ideation through production.
Translate banking and financial services business problems into clear AI system designs, technical requirements, and non-functional requirements with measurable outcomes.
Support GenAI use cases across areas such as customer service, operations, knowledge management, risk, compliance, fraud, employee productivity, document intelligence, and internal workflow automation.
Troubleshoot and resolve complex issues across non-production and production environments.
Partner closely with application teams to ensure AI solutions integrate effectively into existing banking platforms, enterprise workflows, data environments, APIs, and control frameworks.
Influence platform roadmap by feeding real-world banking use-case requirements back into central AI services and enterprise AI platform teams.
<h3 class="jobSectionHeader">Governance, Risk &amp; Compliance</h3>
Ensure all AI solutions align with banking risk, cyber, model governance, data protection, privacy, and regulatory expectations.
Partner with Cyber, Model Risk Management, Legal, Compliance, Risk, and Data Governance teams to design compliant AI patterns without slowing delivery.
Embed security, privacy, responsible AI, ethical AI, explainability, human oversight, and auditability into solution design by default.
Help define practical implementation patterns that balance innovation, speed, governance, regulatory expectations, and enterprise control requirements.
Ensure GenAI solutions are designed with appropriate guardrails for sensitive financial data, customer information, personally identifiable information, and regulated business processes.
<h3 class="jobSectionHeader">Organizational Influence &amp; Mentorship</h3>
Serve as a recognized GenAI expert across the enterprise, regularly consulted by engineering, architecture, product, risk, compliance, and leadership teams.
Mentor senior and staff-level engineers and help raise the technical bar across banking technology teams.
Contribute to internal communities of practice, architecture reviews, executive-level technical discussions, AI governance forums, and knowledge-sharing sessions.
Represent enterprise GenAI capabilities in internal innovation forums, banking technology discussions, and responsible AI showcases.
<h2 class="jobSectionHeader">Required Qualifications</h2>
7+ years of software engineering experience, with significant depth in AI/ML, data-intensive systems, distributed systems, or enterprise-scale platforms.
2+ years of hands-on Python programming experience.
2+ years of experience designing and delivering production-scale Generative AI systems in an enterprise environment.
2+ years of experience with LLMs, prompt engineering, and RAG architecture.
2+ years of experience with vector databases, semantic search, and retrieval systems.
2+ years of experience with API-driven, cloud-native architectures.
2+ years of experience with distributed systems, performance optimization, scalability, and reliability engineering.
Experience working within banking, financial services, fintech, or another highly regulated enterprise environment.
<h2 class="jobSectionHeader">Preferred Qualifications</h2>
Strong understanding of banking technology environments and non-functional requirements, including security, scalability, resiliency, observability, latency, auditability, and cost management.
Demonstrated Principal-level impact, with influence across multiple teams, platforms, business units, or lines of business.
Experience operating in highly regulated environments, with financial services or banking experience strongly preferred.
Hands-on experience with agentic AI frameworks, AI workflow orchestration, and multi-model routing.
Prior experience in a Forward Deployed Engineer, embedded engineering, or business-facing technical delivery model.
Experience partnering with risk, cyber, legal, compliance, data governance, or model governance teams to deliver production AI solutions.
Familiarity with banking controls, customer data protection, model risk management, audit requirements, regulatory expectations, and responsible AI principles.
Ability to communicate complex technical concepts clearly to senior executives, technical stakeholders, risk partners, compliance teams, and non-technical business leaders.
<h2 class="jobSectionHeader">Ideal Candidate Profile</h2>
The ideal candidate is a hands-on Principal-level engineer and architect who can move seamlessly between strategy, architecture, and execution in a banking environment. They are comfortable working directly with business teams to understand real-world financial services problems, while also going deep with engineering teams on system design, performance, security, governance, and production readiness.
This person brings strong technical judgment, enterprise banking delivery experience, and the ability to build practical, compliant GenAI solutions that can scale responsibly across a large financial institution.</div>

Principal AI Engineer

Wells Fargo

<div>About this role:
Wells Fargo is seeking a Principal Engineer to join our AI Platforms and Enterprise Execution Group as part of Consumer Technology. Learn more about the career areas and business divisions at wellsfargojobs.com.
This role focuses on designing and delivering enterprise‑scale strategic initiatives in reusable AI patterns that deliver business and customer value.
This is a hands‑on Principal Engineer role for a technical leader who designs, builds, and scales AI‑driven platforms, while operating at enterprise scope. The Principal Engineer serves as a technical authority who codes, prototypes, and reviews architecture, not just oversees execution 
In this role, you will:<ul><li>
Act as a trusted advisor to leadership, guiding the development and influence of applications, networks, information security, databases, operating systems, web technologies, and emerging AI capabilities to address highly complex business and technical needs across multiple groups</li><li>
Lead the strategy and resolution of highly complex, unique challenges through end‑to‑end solution design, including Generative and Agentic AI systems, cloud‑native platforms, and legacy modernization efforts that require long‑term vision, creativity, innovation, and advanced analytical thinking</li><li>
Translate advanced technology expertise, deep understanding of enterprise business objectives, organizational structure, and the broader technology ecosystem into scalable engineering solutions, such as reusable architectures, AI-enabled platforms, and production‑ready systems</li><li>
Provide vision, direction, and technical leadership to senior leaders on implementing innovative business solutions, embedding AI and automation into product delivery workflows, decision support, and developer productivity while ensuring alignment with security, compliance, and responsible AI standards</li><li>
Maintain deep awareness of industry best practices, emerging technologies, and AI advancements, proactively recommending innovations that modernize operations, improve efficiency and quality, and create competitive advantage for the organization</li><li>
Strategically engage with professionals and managers at all levels of the enterprise, serving as an expert technical advisor and escalation point for complex platform, data, and AI decisions while mobilizing and guiding large‑scale, cross‑organizational initiatives and communicating progress to executive leadership</li></ul> 
Required Qualifications:<ul><li>
7+ years of Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education</li><li>
7+ years of senior engineering experience, including architecture and hands‑on delivery of large‑scale platforms and systems</li><li>
4+ years of experience developing or deploying AI‑powered tools, chatbots, LLM‑based automation, or agentic workflows, including understanding of AI risks, observability needs, and stakeholder communication</li><li>
3+ years of hands‑on experience across Cloud architectures including Google Cloud Platform, Microsoft Azure, AWS, etc. and internal platforms such as Tachyon</li><li>
3+ years of experience operating at both keyboard‑level technical depth and executive‑level technical storytelling</li></ul>
Desired Qualifications:<ul><li>
Experience working within agile product operating models in large enterprise environments, including agile software delivery and cloud infrastructure</li><li>
Financial services experience preferred; Business Banking domain experience is beneficial but not required</li><li>
Demonstrated ability to mentor senior and staff engineers, raising the technical bar of the organization</li><li>
Proven strategic thinking, analytical problem‑solving, and sound technical judgment in fast‑paced settings</li><li>
Proven experience with cloud infrastructure and containerization, including enterprise compute, storage, and IaaS environments</li><li>
Demonstrated curiosity and innovation mindset for advancing Generative and Agentic AI solutions within regulated enterprise contexts</li><li>
Strong organizational savvy and customer centricity, with the ability to navigate complex enterprise structures and align technology to business outcomes</li></ul> 
Job Expectations:<ul><li>
Ability to travel as needed
</li><li>This position offers a hybrid work schedule</li><li>
This position is not eligible for Visa sponsorship</li></ul>
Job Location:
333 Market St - San Francisco, California 94105
300 S. Brevard - Charlotte, North Carolina 28202
2600 S Price Rd - Chandler, Arizona 85286
Pay Range 
Reflected is the base pay range offered for this position. Pay may vary depending on factors including but not limited to demonstrated examples of prior performance, skills, experience, or work location. Employees may also be eligible for incentive opportunities.
$159,000.00 - $305,000.00<div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div>
Benefits
Wells Fargo provides eligible employees with a comprehensive set of benefits, many of which are listed below. Visit Benefits - Wells Fargo Jobs for an overview of the following benefit plans and programs offered to employees.<ul><li>
Health benefits</li><li>
401(k) Plan</li><li>
Paid time off</li><li>
Disability benefits</li><li>
Life insurance, critical illness insurance, and accident insurance</li><li>
Parental leave</li><li>
Critical caregiving leave</li><li>
Discounts and savings</li><li>
Commuter benefits</li><li>
Tuition reimbursement</li><li>
Scholarships for dependent children</li><li>
Adoption reimbursement</li></ul></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div>
Posting End Date:
12 Jul 2026<ul><li>Job posting may come down early due to volume of applicants.</li></ul>
We Value Equal Opportunity
Wells Fargo is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other legally protected characteristic.
Employees support our focus on building strong customer relationships balanced with a strong risk mitigating and compliance-driven culture which firmly establishes those disciplines as critical to the success of our customers and company. They are accountable for execution of all applicable risk programs (Credit, Market, Financial Crimes, Operational, Regulatory Compliance), which includes effectively following and adhering to applicable Wells Fargo policies and procedures, appropriately fulfilling risk and compliance obligations, timely and effective escalation and remediation of issues, and making sound risk decisions. There is emphasis on proactive monitoring, governance, risk identification and escalation, as well as making sound risk decisions commensurate with the business unit&rsquo;s risk appetite and all risk and compliance program requirements.
Applicants with Disabilities
To request a medical accommodation during the application or interview process, visit Disability Inclusion at Wells Fargo.
Drug and Alcohol Policy 
Wells Fargo maintains a drug free workplace. Please see our Drug and Alcohol Policy to learn more.
Wells Fargo Recruitment and Hiring Requirements:
a. Third-Party recordings are prohibited unless authorized by Wells Fargo.
b. Wells Fargo requires you to directly represent your own experiences during the recruiting and hiring process.</div>

Tamarind Bio

<div><h1 class="jobSectionHeader">About Tamarind Bio</h1>
We enable any scientist to access AI-powered drug discovery. Thousands of scientists from large pharma companies, top biotechs, and academic institutions use Tamarind to design protein drugs, improve industrial enzymes, and create cutting edge molecules that weren&rsquo;t feasible until now.
New AI models are quickly eclipsing physics-based tools in computational drug discovery. Scientists often struggle to fine-tune, deploy, and scale these models, leaving breakthroughs on the table. Tamarind provides a simple interface to the vast array of tools being released daily.
Staff Software Engineer / Technical Lead
We're hiring a Staff Software Engineer to provide technical leadership across our engineering team as we continue to scale the platform behind Tamarind.
Today, our engineering team consists primarily of early and mid-career engineers. As the complexity of our systems and customer requirements continues to grow, we're looking for someone who can help guide technical decision-making, mentor engineers, and drive architectural discussions across the organization.
This is not an engineering management role.
We're looking for a hands-on technical leader who enjoys writing code, reviewing designs, solving difficult engineering problems, and helping other engineers grow. You'll work closely with the CTO to shape technical direction while remaining deeply involved in execution.
The role spans architecture, infrastructure, product development, code reviews, technical mentorship, and engineering best practices.
What You'll Do<ul><li>
Partner with the CTO on architecture, technical planning, and major engineering initiatives</li><li>
Provide technical guidance across a team of 7-8 engineers</li><li>
Lead design reviews and architectural discussions</li><li>
Help engineers navigate complex technical challenges</li><li>
Contribute directly to the codebase across infrastructure, backend services, APIs, and product development</li><li>
Review code and provide feedback on implementation approaches</li><li>
Identify opportunities to improve reliability, scalability, performance, and developer productivity</li><li>
Support technical decision-making across new products and platform capabilities</li><li>
Work closely with customers and internal stakeholders to understand requirements and translate them into practical solutions</li><li>
Help establish engineering standards as the team continues to grow</li></ul>
Week in the Life<ul><li>
Collaborate with the CTO on technical priorities and architectural decisions</li><li>
Review designs and provide guidance on implementation approaches</li><li>
Build and operate services across infrastructure, ML systems, APIs, and customer-facing applications</li><li>
Participate in code reviews and technical discussions</li><li>
Help unblock engineers working through difficult technical problems</li><li>
Work directly with customers to understand requirements and gather feedback</li><li>
Balance hands-on engineering work with technical leadership responsibilities</li></ul>
Ideal Qualifications<ul><li>
7+ years of software engineering experience</li><li>
Experience serving as a senior technical contributor, staff engineer, principal engineer, or technical lead</li><li>
Strong software architecture and distributed systems experience</li><li>
Experience building and operating production infrastructure and cloud services</li><li>
AWS experience (EC2, S3, DynamoDB, Docker, etc.)</li><li>
Ability to mentor engineers and provide technical guidance across multiple projects</li><li>
Strong communication skills and sound engineering judgment</li><li>
Comfort operating in an early-stage startup environment</li><li>
Willingness to work onsite in San Francisco</li></ul>
Technology
Our technology sits at the intersection of DevOps, MLOps, and Computational Biology. We support workloads ranging from large-scale ML inference and model deployment to workflow orchestration across research, infrastructure, and scientific computing environments.
The role requires someone who enjoys moving between architecture, implementation, operations, and mentorship while helping a growing engineering team tackle increasingly complex technical challenges.
Compensation Range: $150K - $250K</div>

Staff Software Engineer / Technical Lead

Salesforce

<div>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
Software Engineering
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&rsquo;t a buzzword &mdash; it&rsquo;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&rsquo;re in the right place! Agentforce is the future of AI, and you are the future of Salesforce.
The Experience
 
Salesforce is building the next-generation Enterprise Knowledge Graph platform to power AI-driven experiences, agentic applications, semantic search, enterprise data discovery, and intelligent decision-making across the company. The platform serves as the foundational knowledge layer connecting enterprise data, business entities, ontologies, and relationships across multiple domains.
 
 
We are seeking both a Senior Member of Technical Staff (SMTS) and a Lead Member of Technical Staff (LMTS) to join our Enterprise Knowledge Graph and AI Engineering team.
 
 
The SMTS will serve as a senior engineer and core systems developer &mdash; heavily hands-on, developing, optimizing, and scaling core knowledge graph components, semantic pipeline workflows, and AI-powered frameworks. You will partner with Lead and Principal Engineers to implement technical designs and build production-ready scalable systems that support agentic AI use cases across the enterprise.
 
 
The LMTS will serve as a hands-on technical lead, systems designer, and ontology engineer &mdash; designing, building, and scaling core knowledge graph infrastructure, semantic schemas, and AI-powered developer frameworks. You will partner closely with Principal Engineers, Product Management, Ontology experts, and Data Engineering teams to turn high-level engineering visions into production-ready scalable foundations.
 
 
Both roles will actively implement and drive AI-powered engineering tools and developer platforms that improve engineering productivity, software quality, and delivery velocity across the organization. 
 
What You'll Actually Be Doing
<ul><li>Design &amp; Implement: Build and scale Salesforce's Enterprise Knowledge Graph platform components, focusing on performance, data throughput, system reliability, high availability, and robust data integrity. (LMTS: Lead hands-on design and implementation of platform subsystems; SMTS: Write high-quality, production-grade code.)
</li><li>Graph &amp; Ontology Engineering: Develop graph data models, write complex graph queries, and construct scalable data pipelines to ingest and map structured and unstructured data to enterprise ontologies and taxonomies. (LMTS: Also design enterprise ontologies, taxonomies, semantic layers, entity resolution frameworks, graph APIs, and vector search capabilities to support advanced RAG and agentic workflows.)
</li><li>Semantic Routing: Write and maintain Python-based semantic routing frameworks to parse, classify, and dynamically direct incoming queries to the appropriate knowledge graph indexes or vector databases. (LMTS: Design, optimize, and productionize routing frameworks at enterprise scale, steering queries to appropriate knowledge graphs, ontology sub-graphs, or vector databases.)
</li><li>AI Tooling &amp; Automation: Build, integrate, and leverage AI-powered developer tools and engineering automation platforms utilizing ecosystems such as Claude, Cursor, Windsurf, AI Agents, and Model Context Protocol (MCP) frameworks. (LMTS: Also develop, deploy, and optimize these tools; drive strategy and productionization.)
</li><li>Data Integration: Build scalable data pipelines and engineering patterns to ingest, transform, and orchestrate structured, unstructured, and third-party data sources into graph-based platforms mapped tightly to enterprise ontologies.
</li><li>Feature Ownership &amp; Technical Execution: Own the technical execution of specific platform features from concept through design, coding, testing, and production deployment. (LMTS: Also translate high-level technical visions and roadmaps into concrete system blueprints, ontology schemas, and execution plans.)
</li><li>Code Quality &amp; Rigor: Participate heavily in code reviews, write comprehensive automated unit/integration tests, and ensure adherence to engineering standards and operational best practices.
</li><li>Technical Mentorship: Provide technical guidance and mentorship to engineers on the team. (SMTS: Mentor MTS and Associate engineers. LMTS: Provide day-to-day guidance, code reviews, and design direction to SMTS, MTS, and associate engineers, fostering a culture of technical rigor and operational maturity.)
</li><li>Cross-Functional Collaboration: Work closely with Lead/Principal Engineers, Product Managers, and Data Engineering teams to deliver robust features aligned with broader enterprise AI priorities. (LMTS: Also partner with PMTS engineers and Ontology governance boards to ensure alignment with AI infrastructure standards.)
</li><li>Evaluate &amp; Innovate (LMTS): Conduct deep-dive evaluations of emerging graph technologies, ontology modeling tools, semantic reasoning frameworks, vector databases, and AI tooling to continuously modernize the platform.
</li></ul>You're Our Person If...
SMTS
<ul><li>Experience: 8+ years of hands-on software engineering experience in development, data engineering, distributed systems, or enterprise data platforms.
</li><li>Education: A related technical degree required.
</li><li>Core Programming: Expert-level coding skills in backend ecosystems, with strong fluency in Python and standard object-oriented/functional programming languages.
</li><li>Semantic Routing &amp; AI: Hands-on experience developing and deploying custom semantic routers using Python (leveraging native embeddings, LangChain, or mathematical logic like cosine similarity) alongside RAG architectures, vector search platforms, and AI workflows.
</li><li>Graph &amp; Ontology Fundamentals: Solid experience working with graph databases and semantic web concepts (e.g., Neo4j, RDF/OWL, SPARQL, property graphs) and mapping data to structured taxonomies.
</li><li>Developer Tooling: Practical experience configuring, testing, or integrating AI-assisted engineering tools or automation workflows (e.g., Claude, Cursor, Windsurf, GitHub Copilot, or MCP frameworks).
</li><li>Distributed Systems &amp; Cloud: Proven experience building applications on cloud-native systems (AWS, GCP, or Azure) utilizing microservices, REST/gRPC APIs, and event-driven data streaming (e.g., Kafka).
</li><li>Delivery: Track record of owning and successfully delivering complex features in an agile, production-scale environment.
</li></ul>LMTS
<ul><li>Experience: 10+ years of hands-on experience in software engineering, data engineering, distributed systems, or enterprise data platforms.
</li><li>Education: A related technical degree required.
</li><li>Ontology &amp; Graph Expertise: Solid, hands-on experience designing and building Knowledge Graph platforms, formal ontologies, semantic models, taxonomies, or enterprise metadata management systems.
</li><li>Tooling &amp; Ecosystems: Strong hands-on experience with graph technologies and ontology engineering tools (e.g., Neo4j, TopQuadrant, Prot&eacute;g&eacute;, RDF/OWL, SPARQL, SHACL, property graphs) and semantic reasoning frameworks.
</li><li>AI &amp; Retrieval: Proven experience implementing graph-powered AI solutions, vector search platforms, Retrieval-Augmented Generation (RAG) architectures, and orchestrating agentic workflows.
</li><li>Semantic Routing Mastery: Demonstrated hands-on experience designing, optimizing, and productionizing custom semantic routers using Python (leveraging native embeddings, LangChain, semantic-router, or specialized mathematical logic like cosine similarity) to decouple intent handling from expensive LLM calls.
</li><li>Developer Automation: Experience deploying and integrating AI-assisted engineering tools or automation workflows using ecosystems like Claude, Cursor, Windsurf, GitHub Copilot, or MCP frameworks.
</li><li>Backend &amp; Cloud: Strong experience with cloud-native system designs (AWS, GCP, or Azure), distributed systems, microservices, and high-throughput event-driven systems.
</li><li>Leadership: Demonstrated experience leading feature teams, guiding technical execution, and mentoring mid-to-senior level engineers.
</li></ul>Even Better If...
SMTS
<ul><li>Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
</li><li>Familiarity with ontology validation frameworks (e.g., SHACL) and data quality governance.
</li><li>Experience building integrations with data platform environments like Salesforce Data Cloud or enterprise CRM metadata architectures.
</li><li>Experience optimizing low-latency applications and heavy-throughput vector search lookups.
</li><li>Passion for engineering automation and driving personal/team velocity via advanced AI development tools.
</li></ul>LMTS
<ul><li>Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field with a focus on Semantic Web or Knowledge Representation.
</li><li>Direct experience integrating platforms with Salesforce Data Cloud, CRM platforms, or metadata-driven system designs.
</li><li>Experience with semantic routing at enterprise scale, high-throughput enterprise search systems, and graph-powered recommendation engines.
</li><li>Deep familiarity with advanced ontology governance, federated knowledge management, and data contract alignment.
</li><li>Proven track record of optimizing engineering team velocity through the tailored implementation of AI developer tooling.
</li></ul>Unleash Your Potential
When you join Salesforce, you&rsquo;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&rsquo;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 &mdash; but to redefine what&rsquo;s possible &mdash; 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&rsquo; 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&rsquo;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 &ndash; 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.&amp;#xa;&amp;#xa;The typical base salary range for this position is $148,500 - $260,100 annually. In select cities within the San Francisco and New York City metropolitan area, the base salary range for this role is $178,900 - $285,800 annually.&amp;#xa;&amp;#xa;The range represents base salary only, and does not include company bonus, incentive for sales roles, equity or benefits, as applicable.</div>

Data Engineer (SMTS/LMTS) - Knowledge Graph & AI

David Joseph & Company

<div><h2 class="jobSectionHeader">Founding Engineer &mdash; Confidential (AI Startup, YC/a16z-Backed)</h2>
Location: San Francisco, CA (Onsite, 5 days/week) 
Compensation: $180,000 &ndash; $225,000 base + 1.0% &ndash; 1.5% equity 
Visa Sponsorship: Available &mdash; visa transfers supported | Relocation support available 
Employment Type: Full-Time<h3 class="jobSectionHeader">
About the Company</h3>
A well-funded AI startup building a new paradigm for software creation &mdash; using AI agents to autonomously create and operate specialized software products at scale. Founded in 2026, the company has raised $5.5M from a16z and other top-tier investors and is building out its founding engineering team of 5&ndash;7 engineers. The founding team has previously scaled companies to $20M ARR.<h3 class="jobSectionHeader">
The Role</h3>
This is a founding engineering role for a generalist full-stack engineer who loves building from zero. You will ship micro apps weekly to real users, encode your processes into increasingly automated workflows, and run rapid experiments with the founding team. All engineers report directly to the founder and CEO.<h3 class="jobSectionHeader">
What You'll Own</h3><ul><li>
Build and ship micro apps every week with real users, encoding your processes into increasingly automated workflows</li><li>
Work in close collaboration with the founding team</li><li>
Run rapid experiments and decisively double down on what works while cutting what doesn't</li></ul>
Tech stack: Full-stack, AI &mdash; Python, JavaScript, Kotlin, Go (flexible on language)<h3 class="jobSectionHeader">
Requirements</h3><ul><li>
1&ndash;5 years of software engineering experience building AI-driven products</li><li>
Experience shipping products or features from ideation to real users with significant traction</li><li>
Proficiency in agentic development &mdash; designing and building orchestration pipelines across multiple agents, tools, and services</li><li>
Full-stack proficiency with a backend focus</li><li>
Active user of modern AI tooling (e.g. Claude Code, Cursor, or similar)</li><li>
At least one clear signal of excellence &mdash; hackathon wins, side projects with significant traction, impressive fellowships, YC founder background, etc.</li><li>
Bachelor's degree in Computer Science or a related technical field</li><li>
Must be based in or willing to relocate to San Francisco</li></ul><h3 class="jobSectionHeader">
Preferred</h3><ul><li>
Previous founder or early-stage startup experience &mdash; YC or a16z alum backgrounds a strong plus</li><li>
Degree from a top-tier university (Berkeley, Stanford, CMU, or equivalent)</li></ul><h3 class="jobSectionHeader">
This Role Is NOT For</h3><ul><li>
Pretraining or fine-tuning ML researchers &mdash; this is applied agentic engineering, not model training</li><li>
Pure Big Tech careers with no side project, startup, or scrappy chapter</li><li>
Candidates with a pattern of short tenures across multiple companies</li></ul><h3 class="jobSectionHeader">
Interview Process</h3><ul><li>
Application review</li><li>
Intro screen (45 min) &mdash; technical depth, past projects, judgment, and founder fit</li><li>
Pair coding session (60 min) &mdash; live coding, no AI tools; CS fundamentals and algorithmic reasoning</li><li>
Onsite (~4 hours) &mdash; agentic coding session, system design, and behavioral/founder-fit conversation</li><li>
Offer</li></ul><h3 class="jobSectionHeader">
Logistics</h3><ul><li>
Role is fully onsite in San Francisco (SoMa) &mdash; 5 days/week</li><li>
Relocation support available</li><li>
Visa sponsorship available</li></ul>
Shortlisted candidates will be contacted by David Joseph &amp; Co., the recruiting partner managing this search.</div>

Founding Engineer — Confidential

Workato

<div><div><h1 class="jobSectionHeader">About Workato</h1>

Workato delivers enterprise infrastructure for the agentic era, redefining iPaaS and helping enterprises unify data, applications, processes, and AI into a single, governed platform. A leader in Enterprise MCP and trusted by 50% of the Fortune 500, Workato&rsquo;s cloud-native architecture connects every application, data source, and process to power real-time orchestration at scale. With enterprise-grade security and continuous innovation at its core, Workato provides the trusted foundation for organizations to automate with confidence and operationalize AI across the business. To learn more, visit www.workato.com
<h1 class="jobSectionHeader">
Why join us?</h1>

Ultimately, Workato believes in fostering a flexible, trust-oriented culture that empowers everyone to take full ownership of their roles. We are driven by innovation and looking for team players who want to actively build our company.

But, we also believe in balancing productivity with self-care. That&rsquo;s why we offer all of our employees a vibrant and dynamic work environment along with a multitude of benefits they can enjoy inside and outside of their work lives.

If this sounds right up your alley, please submit an application. We look forward to getting to know you!

Also, feel free to check out why:
<ul>
<li>Business Insider named us an &ldquo;enterprise startup to bet your career on&rdquo;
</li>
<li>Forbes&rsquo; Cloud 100 recognized us as one of the top 100 private cloud companies in the world
</li>
<li>Deloitte Tech Fast 500 ranked us as the 17th fastest growing tech company in the Bay Area, and 96th in North America
</li>
<li>Quartz ranked us the #1 best company for remote workers
</li>
</ul></div><div><h2 class="jobSectionHeader">Senior AI Engineer &ndash; Developer Products</h2>

Location: San Francisco, CA (Onsite/Hybrid)
<h3 class="jobSectionHeader">
About the Role</h3>

We are seeking an exceptional Senior Software Engineer to join our San Francisco team and build new developer products. In this role, you will design, build, and optimize AI-first experiences that empower developers to experiment, prototype, and integrate with our platform. You will collaborate closely with product, engineering, and developer relations teams to deliver robust, scalable, and intuitive services. This role requires a high technical bar, plus an emphasis on developer ergonomics, so we can deliver a delightful developer experience.
<h3 class="jobSectionHeader">
Responsibilities</h3>
<ul><li>Design, build, and enhance AI services and APIs powering our developer sandbox, leveraging LLMs and custom ML models.</li>
<li>Develop well-architected, testable, and efficient Python code to support rapid prototyping and experimentation.</li>
<li>Implement and improve validation, monitoring, and observability for ML services within the sandbox environment.</li>
<li>Drive the full development lifecycle: from ideation and architecture to deployment and continuous improvement.</li>
<li>Collaborate with cross-functional teams to design developer-centric solutions and intuitive user experiences.</li>
<li>Continuously evaluate and optimize existing implementations for performance, scalability, and developer usability.</li>
<li>Identify and resolve bottlenecks, bugs, and technical challenges in a fast-paced, iterative environment.</li>
<li>Conduct code reviews and mentor team members to uphold high engineering standards.</li>
</ul><h3 class="jobSectionHeader">Requirements</h3>
<h4 class="jobSectionHeader">Qualifications / Experience / Technical Skills</h4>
<ul><li>Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Engineering, Information Systems, or equivalent industry experience.</li>
<li>5+ years of experience as an ML Engineer, Data Scientist, or similar role.</li>
<li>Strong Python programming skills and hands-on experience with NLP and LLM models.</li>
<li>Proven track record of deploying and maintaining ML services in production environments.</li>
<li>Solid understanding of network protocols, API design, and developer tooling.</li>
<li>Experience with relational and non-relational databases.</li>
<li>LLMops/MLops experience is a strong plus, especially in developer-facing products.</li>
<li>Experience building or supporting developer platforms, APIs, or sandbox environments is highly desirable.</li>
</ul><h4 class="jobSectionHeader">Soft Skills / Personal Characteristics</h4>
<ul><li>Collaborative team player with a passion for empowering developers and improving developer experience.</li>
<li>Adaptable, proactive, and creative&mdash;comfortable working in a dynamic, startup-like environment.</li>
<li>Strong problem-solving skills and a continuous improvement mindset.</li>
</ul>
Join us in San Francisco and help shape the future of developer innovation with AI-powered sandbox experiences! 
 
The salary range for this role is dependent on experience and ranges from $170,000 to $250,000. We also provide stock options to all employees and generous benefits.</div></div>

Senior AI Engineer – Developer Products

Resourceful Talent Group

<div>Compensation: $185,000 to $260,000 base + meaningful early-stage equity
About the Role
We are hiring a Founding Product Engineer for our client, a well-funded, fast-growing AI startup that is transforming how professional services firms operate through intelligent automation.
With strong customer traction, paying clients already using the product, and an ambitious roadmap ahead, they&rsquo;re looking for an exceptional engineer who wants to help build a category-defining product from the ground up. This is a rare opportunity to work directly with the founding team, take ownership of core product development, and play a key role in shaping both the product and the engineering culture.
What You&rsquo;ll Do<ul><li>
Build and ship product features across the full stack, from concept to production</li><li>
Design scalable frontend and backend solutions using modern web technologies</li><li>
Develop integrations with third-party platforms and APIs</li><li>
Build AI-powered features using LLMs and agent-based workflows</li><li>
Collaborate closely with the founders on product strategy, technical decisions, and roadmap planning</li><li>
Move quickly, solve complex problems, and continuously improve the product based on customer feedback</li></ul><ul><li>
2 to 7 years of professional software engineering experience</li><li>
Strong experience with TypeScript, React, Next.js, Node.js, and SQL or PostgreSQL</li><li>
Experience building and shipping production-ready full-stack applications</li><li>
Hands-on experience working with LLMs, AI tools, or agentic systems</li><li>
Ability to take ownership and thrive in a fast-paced startup environment</li><li>
Strong product mindset and passion for building user-focused software</li><li>
Excellent communication and problem-solving skills</li></ul>
Nice to Have<ul><li>
Experience working at a seed or Series A startup</li><li>
Experience building API integrations or workflow automation tools</li><li>
Exposure to AI-first products or automation platforms</li><li>
Previous experience as an early engineering hire or working directly with founders</li></ul>
Why Join?<ul><li>
Competitive base salary of $185K to $260K</li><li>
Meaningful early-stage equity</li><li>
Opportunity to become one of the first engineering hires</li><li>
Work directly with experienced founders who have successfully built and scaled startups</li><li>
Join a company with proven market demand and paying customers</li><li>
Hybrid schedule in San Francisco (3 days in office)</li><li>
Relocation assistance available</li><li>
Visa transfer support for qualified candidates</li><li>
High-impact role with significant ownership and opportunities for growth</li></ul></div>

Founding Product Engineer

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