Software Engineering Pmts

Salesforce Salesforce · Enterprise · Bangalore, India

Senior Engineering contributor on the Agentforce platform team, owning the architecture, design, and execution of the Agentic AI platform and applications. Collaborates with software engineers, data scientists, product managers, and data teams to build and turn cutting-edge architecture and research into scalable, production-ready systems. Focuses on backend systems, data pipelines for training and inference, translating user needs into technical requirements, setting technical direction, mentoring engineers, and driving ML best practices.

What you'd actually do

  1. Lead architecture and development of AI-powered backend systems and services.
  2. Design and optimize data pipelines for training and inference at scale.
  3. Work with product and business teams to translate user needs into technical requirements.
  4. Set technical direction and mentor engineers across teams.
  5. Drive adoption of ML best practices for model training, deployment, monitoring, and governance.

Skills

Required

  • software engineering
  • AI/ML systems
  • object oriented programming
  • Python
  • Applied AI
  • AI applications
  • ML frameworks
  • PyTorch
  • TensorFlow
  • scikit-learn
  • LLMs
  • vector databases
  • generative AI
  • OpenAI
  • LangChain
  • LlamaIndex
  • RAG pipelines
  • system design
  • distributed systems
  • cloud-native architectures
  • AWS
  • GCP
  • Agentic AI experiences
  • ML pipelines
  • data engineering workflows
  • API platforms
  • cross-functional teams
  • mentoring engineers
  • communication skills
  • collaboration skills
  • complex AI concepts
  • startups
  • high-growth tech companies

Nice to have

  • Contributions to open-source AI/ML projects
  • Patents
  • papers
  • blogs
  • external publications
  • startup mindset
  • innovation-first projects

What the JD emphasized

  • 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.

Other signals

  • building and turn cutting-edge architecture and research into scalable, production-ready systems
  • build and deploy ML models
  • 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