Autonomy Engineer

Caterpillar Caterpillar · Industrial · Bangalore, Karnataka +1

Autonomy Engineer at Caterpillar focused on designing, building, and iterating on GenAI solutions including LLM-based systems, RAG, agents, and multimodal use cases. Responsibilities include data exploration, feature engineering, model training, evaluation, and implementing scalable, maintainable solutions with a strong emphasis on Responsible AI controls like prompt management, guardrails, and data provenance. The role involves contributing production-ready code and artifacts, supporting the transition from PoC to production, and collaborating with various engineering and product teams.

What you'd actually do

  1. Design, build, test, and iterate on data science, machine learning, and Generative AI (GenAI) solutions aligned to pod objectives, including LLM‑based systems, retrieval‑augmented generation (RAG), agents, and multimodal use cases.
  2. Perform data exploration, feature engineering, model training, evaluation, and validation, including GenAI‑specific evaluation (e.g., groundedness, hallucination risk, latency, cost, and quality metrics).
  3. Implement solutions that are scalable, maintainable, and aligned with enterprise architecture, data, and engineering standards, with explicit consideration for GenAI safety, security, and Responsible AI controls (prompt management, guardrails, data provenance, and access controls).
  4. Contribute production‑ready code, notebooks, pipelines, and model artifacts, including prompts, system instructions, evaluation harnesses, and GenAI configuration assets.
  5. Execute assigned work items to meet sprint and increment commitments aligned to the product roadmap.

Skills

Required

  • Python
  • SQL
  • Prompt engineering
  • Data Science & ML Foundations
  • Programming & Tooling
  • Data‑Informed Problem Solving
  • Agile Delivery
  • Communication & Collaboration
  • Knowledge of AI and Generative AI concepts
  • Knowledge of relevant programming languages and tools

Nice to have

  • Advanced degree (Master’s or PhD) in artificial intelligence, machine learning, engineering, mathematics, physics, or a closely related field

What the JD emphasized

  • GenAI safety
  • security
  • Responsible AI controls
  • prompt management
  • guardrails
  • data provenance
  • access controls

Other signals

  • design, build, test, and iterate on data science, machine learning, and Generative AI (GenAI) solutions
  • LLM‑based systems, retrieval‑augmented generation (RAG), agents, and multimodal use cases
  • Perform data exploration, feature engineering, model training, evaluation, and validation
  • Implement solutions that are scalable, maintainable, and aligned with enterprise architecture
  • explicit consideration for GenAI safety, security, and Responsible AI controls (prompt management, guardrails, data provenance, and access controls)