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Cargill

Senior Software Engineering - Ag & Trading

Bengaluru, India · Shanghai, ChinaPosted 19 days ago

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Why you should apply for a job to Cargill:

4.1/5 in overall job satisfaction
4.5/5 in supportive management
71% say women are treated fairly and equally to men
71% would recommend this company to other women
79% say the CEO supports gender diversity

Ratings are based on anonymous reviews by Fairygodboss members. See all reviews ›

Job Purpose and Impact

The Senior Software Engineering - Ag & Trading for AI Assistants & Agents in AI & Data Science builds services to operate Cargill's portfolio of GenAI Assistants and Agents - including ChatGPT-powered copilots and bespoke LLM services. You will translate product requirements into secure, efficient, and observable services and or agents; manage the lifecycle from experiment to production; and continually improve reliability, latency, and cost. Typical deliverables span REST services, vector-search back end, LLMOps & AgentOps pipelines, and rich front-end components for knowledge workers and plant operators. Expect to collaborate daily with product managers, data scientists, cloud engineers, and security teams while acting as the technical authority for GenAI feature design and launch.

Key Accountabilities

Design & Build
- Develop multi-agent workflow automation patterns using Agentic AI
- Process redesign and mapping to agentic workflow patterns
- Architect scalable micro-services that wrap LLM/RAG/Agent workflows (Python).
- Implement robust prompt-engineering patterns, retrieval pipelines, and caching for AI Assistants and AI Agents
Platform Ops
- Extend evaluation, automated testing, canary rollout, and rollback for AgentOps.
- Profile inference latency, GPU/CPU utilization, and memory; deliver quarterly cost-to-serve reductions
- Lead bug-fix, security-patch, and performance-tuning sprints for live AI Assistants and AI Agents
Operational Excellence
- Own on-call runbooks, SLOs, and incident reviews; embed observability
- Enforce Responsible-AI guardrails, data-privacy controls, and vulnerability-management policies for AI Assistants and AI agents
Enablement & Mentoring
- Coach full-stack and data-science peers on GenAI/LLMOps patterns; create internal workshops and tech blogs.

Qualifications

Minimum: 4 years building production software or data platforms .
Typical: 5-8 years, including 2+ years with cloud-native AI/ML or GenAI systems (Azure, AWS, or GCP) or 2+ years of software devlopment
Experience building and scaling full-stack applications using the following languages/frameworks: React & typescript, Java (Spring Boot) and/or Python
Preferred:
- Experience building AI solutions, working with AI tools like Claude Code, GitHub Copilot, etc.
- Experience with building applications that use large language models or other AI services
- Working with AI coding assistants or agentic development tools
- Strong foundation in relational databases, with hands‑on experience using PostgreSQL
- Experience with CI/CD pipelines and modern DevOps delivery practices
- Experience deploying and operating applications on cloud‑native platforms
- Proficiency with Git‑based version control and collaborative development workflows
- Understanding of modern application architectures, cloud‑native patterns, and security best practices

About Cargill

Cargill provides food, ingredients, agricultural solutions and industrial products to nourish the world in a safe, responsible and sustainable way.

Size: 10,000+ employees
Industry: Natural Resources: Agriculture and Food Processing

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