Description

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. 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!

About the Team — Life Sciences Cloud

Salesforce Life Sciences Cloud is purpose-built for pharmaceutical, biotech, medical device, and healthcare companies — helping them accelerate innovation, improve patient outcomes, and streamline commercial operations. Our engineering team builds industry-specific solutions across clinical data management, HCP engagement, patient services, and regulatory workflows, all powered by Salesforce's AI + Data + CRM platform and Agentforce.

We work in a deeply collaborative, cross-functional environment with Data Scientists, UX Designers, Product Managers, and domain experts — building enterprise-grade solutions that directly impact people's lives.

Role Description

We are hiring Software Engineers across multiple levels — MTS, SMTS, and LMTS — on the Life Sciences Cloud team. Whether you are a strong individual contributor, a seasoned technical lead, or a force-multiplying engineering leader, we want to hear from you. The level of the role will be determined based on your experience, scope of impact, and technical depth.

Your Impact — You Will:

Build and ship high-quality, production-grade software using modern engineering practices, with AI as a core part of your development workflow — pushing the boundaries of AI development tools to deliver secure, optimized, and high-quality code
Design and orchestrate complex systems where AI agents integrate seamlessly into life sciences human workflows — spanning clinical data, HCP engagement, patient services, and regulatory operations — driving efficiency and innovation at scale
Contribute to building and maintaining the shared system context, an explicit repository of system designs, constraints, and standards that enables AI to operate accurately and reliably
Critically evaluate code (human or AI-generated) for correctness, quality, security, and performance
Collaborate with Product, UX, and domain experts to translate complex regulatory and compliance requirements (HIPAA, 21 CFR Part 11, GxP) into scalable, production-ready software
Participate across the full software development lifecycle — design, development, code review, testing, deployment, and monitoring
Write automated unit, integration, and functional tests as a standard part of your engineering practice

At SMTS and above, you will additionally:

Lead technical design and architecture decisions for significant features and systems on Life Sciences Cloud
Mentor and uplevel engineers through meaningful code reviews, hands-on guidance, and technical coaching
Drive service ownership — proactively monitor production systems and lead incident resolution

At LMTS, you will additionally:

Define technical strategy and multi-quarter architecture roadmaps, influencing platform-wide decisions across the Life Sciences vertical
Develop each engineer's ability to work effectively in an AI-augmented environment, coaching growth into higher-level system design and architecture work
Own how AI tools are integrated into the team's daily development cycle — including configuration, feedback loops, and judgment calls about when human review is required
Serve as the guardian of architectural integrity, security best practices, and technical standards as AI increases code volume — coaching engineers to critically audit AI-generated code for logic flaws, vulnerabilities, and performance issues
Act as a technical partner to senior Product, Design, and domain leadership to translate strategic Life Sciences initiatives into engineering reality

Required Skills:

3+ years of software engineering experience (MTS: 3–5 yrs / SMTS: 5–8 yrs / LMTS: 8+ yrs) with a proven track record of shipping production-quality software
Strong proficiency in one or more of Java, Python, Go, or JavaScript/TypeScript for scalable backend or full-stack development
Deep understanding of data structures, algorithms, and software design principles
Solid experience with RESTful API design, microservices architecture, and distributed systems
Experience with relational and/or NoSQL databases, query optimization, and data modeling
Familiarity with cloud infrastructure and deployment practices (AWS, GCP, or Azure)
Experience with CI/CD pipelines, version control (Git), and modern DevOps practices
A demonstrated, genuine AI-first approach to engineering — using AI tools to move faster, build fluency across the stack, and contribute well beyond your core specialty
Hands-on experience with AI-assisted development tools (e.g., Claude Code, GitHub Copilot, Cursor, Codex, etc.)
Advanced prompt engineering skills — ability to write precise, structured prompts and cultivate the system context that makes AI outputs reliable, secure, and production-ready

At LMTS, additionally required:

Active, hands-on proficiency with AI development tools at full utilization — with the technical depth to evaluate architectural integrity and make informed decisions about AI-generated output
Proven track record of influencing technical direction across multiple teams and driving org-level engineering decisions

Preferred Skills:

Life sciences or healthcare domain knowledge — clinical trials, pharma commercial operations, medical devices, HL7/FHIR, HIPAA/GxP compliance
Familiarity with regulated software environments — 21 CFR Part 11, Computer System Validation (CSV), CDISC, RTSM, or EDC systems
Experience building AI/ML integrations or agentic solutions at production scale
Salesforce platform familiarity — Apex, LWC, Agentforce (nice to have, not required)

Posting Statement

Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. 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.

Key changes made:

Required Skills now purely covers core SWE fundamentals — Java/Python/Go/JS, distributed systems, databases, cloud, CI/CD
Salesforce platform skills (Apex, LWC, etc.) moved to Preferred and framed as "nice to have"
Kept the full AI Fluency language intact across all three levels