Senior AI/ML DevOps Platform & SDLC Automation Architect | 12+ Yrs | Any UST Location | Immedia[...]

UST; Bengaluru; On-site; INR 1,500,000 - 2,500,000; Full time

Job summary

UST is seeking an experienced software engineer with a robust background in AI/ML architecture and DevOps. Candidates must have over 12 years of experience in software engineering, cloud technologies, and strong expertise in AI automation. Key responsibilities include designing solutions for AI applications, integrating REST APIs, and managing CI/CD pipeline automation. Candidates familiar with Azure cloud and observability tooling like Prometheus and Grafana are preferred. Immediate joiners will be prioritized.

Qualifications

• 12+ years of overall experience in software engineering, architecture, DevOps, platform engineering, or enterprise automation.
• Hands-on experience in designing agentic AI solutions and API integrations.
• Strong experience with cloud platforms, especially Azure.

Skills

AI/ML architecture

DevOps

REST API design

CI/CD pipeline automation

Cloud experience in Azure

Observability tooling

Agentic AI solutions

Strong communication

Tools

Prometheus

Grafana

LangChain

LlamaIndex

CrewAI

AutoGen

Job description

Candidates ready to join immediately can share their details via email for quick processing.

[e-mail]

Must-Have Skills:

• 12+ years of overall experience in software engineering, architecture, DevOps, platform engineering, or enterprise automation
• Strong expertise in AI/ML architecture and AI automation
• Hands-on experience in designing agentic AI solutions and multi-step workflow automation
• Strong experience in REST API design, integration, and service-based architecture
• Experience building LLM-powered enterprise applications
• Hands-on experience with RAG architectures, embeddings, prompt engineering, and enterprise AI workflows
• Experience with orchestration frameworks such as LangChain, LlamaIndex, CrewAI, or AutoGen
• Strong understanding of DevOps platforms and engineering workflows
• Experience in CI/CD pipeline automation, source control workflows, and infrastructure automation
• Experience implementing governance, compliance, repository policies, and security automation
• Strong experience with Prometheus, Grafana, and observability tooling
• Cloud experience in Azure is required; AWS/GCP exposure is an advantage
• Strong communication, architecture discussion, and stakeholder management skills

Good-to-Have Skills:

• Experience building multi-agent AI architectures
• Familiarity with AI evaluation, monitoring, and guardrail frameworks
• Experience with vector databases and semantic search systems
• Experience building enterprise knowledge retrieval systems
• Exposure to internal developer platforms or engineering enablement platforms
• Experience building engineering dashboards, operational monitoring tools, or platform portals
• Familiarity with secure AI integrations, governance frameworks, and compliance automation
• Exposure to LLMOps / MLOps / AI platform engineering practices
• Experience working in large-scale enterprise cloud environments

Key Skills: