Description
We’re Salesforce, the Customer Company, inspiring the future of business with AI+ Data+CRM. Leading with our core values, we help companies across every industry blaze new trails and connect with customers in a whole new way. And, we empower you to be a Trailblazer, too — driving your performance and career growth, charting new paths, and improving the state of the world. If you believe in business as the greatest platform for change and in companies doing well and doing good– you’ve come to the right place.
About Agentforce
At Salesforce, Agentforce embodies our commitment to leveraging AI, data analytics, and CRM to revolutionize business operations. Agentforce integrates advanced AI capabilities and real-time data insights to deliver Agentic AI solutions. Designed to enhance productivity, streamline workflows, and provide actionable intelligence, Agentforce ensures that organizations can augment their workforces with digital labor. Upholding the highest standards of trust and security, Agentforce empowers businesses to build stronger customer relationships, drive growth, and achieve their goals with unparalleled efficiency and reliability.
Role Description
As a Senior Engineering contributor on the Agentforce platform team, you will own the architecture, design, and execution of our Agentic AI platform and applications. You’ll collaborate closely with software engineers, data scientists, product managers, and data teams to build and turn cutting-edge architecture and research into scalable, production-ready systems.
You are not just a coder — you are a thought leader, innovator, builder and mentor who thrives on ownership and pushing boundaries in applied machine learning and software engineering, in a rapidly changing and cutting edge space.
Key Responsibilities
Lead architecture and development of AI-powered backend systems and services.
Design and optimize data pipelines for training and inference at scale.
Work with product and business teams to translate user needs into technical requirements.
Set technical direction and mentor engineers across teams.
Drive adoption of ML best practices for model training, deployment, monitoring, and governance.
Innovate in model building,but in how models are trained,deployed,and monitored
Make strategic technical decisions on build vs buy, model selection, and infrastructure.
Required Skills
14+ years of software engineering experience; 3+ years building AI/ML systems at scale
Expertise in at least one object oriented programming language (Java/C++) and one ML native language (Python).
Strong hands-on experience in coding and building Applied AI and AI applications.
Deep experience with ML frameworks like PyTorch, TensorFlow, or scikit-learn.
Familiarity with LLMs, vector databases, and applied generative AI (e.g., OpenAI, LangChain, LlamaIndex, RAG pipelines).
Strong background in system design, distributed systems, and cloud-native architectures (AWS/GCP).
Experience in building and scaling Agentic AI experiences, ML pipelines, data engineering workflows, and API platforms.
Proven ability to lead cross-functional teams and mentor engineers.
Strong communication and collaboration skills across technical and non-technical teams.
Ability to translate complex AI concepts into pragmatic engineering decisions
Experience in startups or high-growth tech companies.
Preferred Skills
Contributions to open-source AI/ML projects
Patents, papers, blogs, or other external publications
Strong startup mindset demonstrated by innovation-first projects