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トレンド企業

トレンド企業

採用

求人Cargill

Senior Software Engineer-AI

Cargill

Senior Software Engineer-AI

Cargill

Bangalore, Karnataka, India

·

On-site

·

Full-time

·

1d ago

Job Purpose and Impact

The Software Engineering Senior Professional will lead the design, build, and ongoing support of complex AI Assistants, AI Agents, and automation solutions—leveraging ChatGPT‑based copilots, Copilot Studio agents, and Power Automate workflows—while adhering to Food EMEA AI CoE platform standards and guardrails. Deliverables typically span API and integration services, retrieval and vector‑search pipelines, enterprise‑scale LLMOps/Agent Ops operational tooling, and intuitive front‑end experiences for both office users and plant operators.

This role will work primarily within the Food EMEA Digital Technology and Data team, owning and shaping solutions across the Food EMEA technology stack that serve Food EMEA teams and customers. In this role, you’ll act as a technical leader and trusted partner to the business Product Owner, with a strong emphasis on translating complex product requirements into secure, scalable, observable, and cost‑efficient services or agents; managing the lifecycle from experiment to production; and proactively driving improvements in reliability, latency, and cost.

Key Accountabilities

  • 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
  • Profile inference latency, GPU/CPU utilization, and memory
  • Writes and maintains highly complex unit tests and integration tests, and performs debugging to maintain the quality and performance of the software/AI solutions
  • Lead bug-fix, security-patch, and performance-tuning sprints for live AI Assistants and AI Agents
  • Leads the establishment and maintenance of comprehensive documentation for agents, applications, deployment processes and system configurations.
  • Own on-call runbooks, SLOs, and incident reviews; embed observability
  • Leads and mentors technical support and troubleshooting for highly complex issues with deployed applications to ensure minimal downtime and fast resolution.
  • Leads cross functional team of engineers to gather requirements and deliver solutions that meet business needs.
  • Experience working within product and agile delivery frameworks including backlog management and cross-functionality delivery and full E2E engineering.
  • Experience with enterprise architecture, data governance, or security standards in the context of digital solution delivery as part of E2E engineering and solution architecture.
  • Experience with digital technologies in the commercial & sales management capability (e.g. Salesforce, Service Cloud, CPQ, Salesloft, ChatGPT or similar platforms)

Qualifications

  • Minimum requirement of 4 years of relevant work experience. Typically reflects 5 years or more of relevant experience.
  • Typically reflects 4 years or more with 3+ years of cloud-native AI/ML or GenAI systems (Azure, AWS, or GCP) or 2+ years of software development.

総閲覧数

0

応募クリック数

0

模擬応募者数

0

スクラップ

0

Cargillについて

Cargill

Cargill

Public

Multinational food company.

10,001+

従業員数

Minnetonka

本社所在地

レビュー

3.3

10件のレビュー

ワークライフバランス

3.5

報酬

3.2

企業文化

3.8

キャリア

3.5

経営陣

2.8

65%

友人に勧める

良い点

Good corporate culture and team environment

Good benefits and compensation

Safety emphasis and good work environment

改善点

Management issues and high turnover

Non-competitive salary

High stress and overwhelming expectations

給与レンジ

268件のデータ

Junior/L3

L2

L3

L4

L5

L6

Mid/L4

Senior/L5

Junior/L3 · Business Analyst

0件のレポート

$108,285

年収総額

基本給

-

ストック

-

ボーナス

-

$92,042

$124,528

面接体験

2件の面接

難易度

3.0

/ 5

期間

14-28週間

面接プロセス

1

Application Review

2

HR Screen

3

Hiring Manager Interview

4

Panel Interview

5

Offer

よくある質問

Behavioral/STAR

Past Experience

Culture Fit

Technical Knowledge