Adobe Systems

2 weeks ago

Software Development Engineer.5

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 4 hours agoStatus: Live

Job Summary

Develop an AI-first engineering platform that automates operations and supports AI-powered decision-making at enterprise scale. Build and scale LLM-powered application platforms, AI agents and MCP servers, secure AI gateways, and RAG pipelines. Create production inference and MLOps/LLMOps capabilities on Kubernetes with CI/CD, observability, and intelligent anomaly detection. Advance autonomous incident investigation and platform engineering across multi-region infrastructure.

Location: Bengaluru

Workplace: Onsite

Employment Type: Full time

Job Function: Product Management

Seniority: Mid level

Key Responsibilities

•Design and build enterprise AI platforms to deploy, operate, and scale LLM-powered applications.
•Develop AI agents, MCP servers, secure AI gateways, and RAG pipelines using enterprise knowledge bases.
•Build production inference and LLM workload platforms on Kubernetes, including scalable GPU-enabled infrastructure and AI CI/CD with automated testing and rollouts.
•Create AI observability capabilities (latency, token utilization, cost, hallucination detection, tracing, and agent execution monitoring) and intelligent anomaly detection.
•Implement autonomous operations for incident investigation, root cause analysis, remediation, capacity optimization, and predictive failure analysis.

Key Requirements

•Practical experience building AI-native applications with tools such as OpenAI APIs, Anthropic Claude, LangGraph/LangChain, MCP, RAG, and AI evaluation frameworks.
•Experience with LLMOps/MLOps including model serving, ML pipelines, feature stores, model monitoring, and related ecosystems (e.g., MLflow, Kubeflow, Ray, KServe, Triton, NVIDIA).
•Strong platform engineering experience with Kubernetes, AWS, Terraform, Docker, Helm, ArgoCD, and GitOps.
•Excellent programming skills in Python and Golang, with experience building distributed systems and APIs.
•Observability experience using Prometheus, Grafana, OpenTelemetry, Jaeger, New Relic, and Elastic.

Experience:LLMOpsMLOpsPlatform engineeringAI observability

Tech Stack:LLMsAI AgentsMCP (Model Context Protocol)RAG (Retrieval-Augmented Generation)Vector DatabasesKubernetesAWSTerraformGitOpsArgoCDService MeshPlatform APIsInternal Developer PlatformsMulti-region infrastructurePythonGolangCI/CDMLflowKubeflowRay

Company Brief

Adobe Systems

Provides creative, marketing, and document management software and cloud services, including Photoshop, Illustrator, Acrobat, and the Adobe Experience Cloud, serving creative professionals, enterprises, and governments worldwide.

Industry: SaaS

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: San Jose, United States

Founded: 1982

Glassdoor: 4.0

Website LinkedIn Glassdoor

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Adobe Systems

2 weeks ago

Software Development Engineer.5

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 4 hours agoStatus: Live

Job Summary

Location: Bengaluru

Workplace: Onsite

Employment Type: Full time

Job Function: Product Management

Seniority: Mid level

Key Responsibilities

•Design and build enterprise AI platforms to deploy, operate, and scale LLM-powered applications.
•Develop AI agents, MCP servers, secure AI gateways, and RAG pipelines using enterprise knowledge bases.
•Build production inference and LLM workload platforms on Kubernetes, including scalable GPU-enabled infrastructure and AI CI/CD with automated testing and rollouts.
•Create AI observability capabilities (latency, token utilization, cost, hallucination detection, tracing, and agent execution monitoring) and intelligent anomaly detection.
•Implement autonomous operations for incident investigation, root cause analysis, remediation, capacity optimization, and predictive failure analysis.

Key Requirements

•Practical experience building AI-native applications with tools such as OpenAI APIs, Anthropic Claude, LangGraph/LangChain, MCP, RAG, and AI evaluation frameworks.
•Experience with LLMOps/MLOps including model serving, ML pipelines, feature stores, model monitoring, and related ecosystems (e.g., MLflow, Kubeflow, Ray, KServe, Triton, NVIDIA).
•Strong platform engineering experience with Kubernetes, AWS, Terraform, Docker, Helm, ArgoCD, and GitOps.
•Excellent programming skills in Python and Golang, with experience building distributed systems and APIs.
•Observability experience using Prometheus, Grafana, OpenTelemetry, Jaeger, New Relic, and Elastic.

Experience:LLMOpsMLOpsPlatform engineeringAI observability

Company Brief

Adobe Systems

Industry: SaaS

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: San Jose, United States

Founded: 1982

Glassdoor: 4.0

Website LinkedIn Glassdoor