Solution Lead - AI Engineer

UPS; Chennai; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

UPS is seeking a strategic and hands-on Lead AI Platform & Automation Engineer to own and scale our enterprise AI platforms, including IBM watsonx and Google Vertex AI, with governance across ML workloads. The role also involves leading a team responsible for day-to-day AI model onboarding, pipeline automation, DevSecOps integration, BI tooling, and AI governance.

This is a high-impact leadership position requiring deep technical expertise, cross-functional collaboration with engineering, data

Qualifications

• 8+ years in cloud engineering, MLOps, or platform leadership.
• 3+ years leading enterprise platform delivery and infrastructure automation.
• Proven experience managing IBM watsonx and Vertex AI in production environments.
• Hands-on delivery of secure, automated pipelines using Terraform, GitOps, and containerized workflows.
• Experience implementing AI governance and compliance using commercial tools and internal frameworks.
• Familiarity with BI tools (Power BI, Looker) and semantic modeling techniques.

Responsibilities

• Platform Leadership: lead owner of IBM watsonx and Vertex AI platforms, governance and operational maturity.
• AI & ML Pipeline Automation: architect and manage CI/CD and MLOps pipelines for training, deployment and data ingestion.
• Agentic AI Enablement: design pipelines for agentic AI systems and integrate with platform capabilities.
• AI Governance: define model approval workflows, metadata tracking, bias detection and explainability.
• DevSecOps & Automation: embed security gates and vulnerability scans into CI/CD workflows.
• Business Intelligence & Semantic Modeling: guide BI teams using Power BI and Looker and standardize data models.
• Team Leadership: mentor cross-functional teams and set goals and best practices for scalable operations.

Skills

Cloud leadership

MLOps

Team leadership

Platform delivery

Education

Bachelor's/Master's in CS/Engineering

Tools

Terraform

Ansible

GitHub Actions

GitLab CI

Azure DevOps

Job description

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Job Description:

Job Summary

We are looking for a strategic and hands‑on Lead AI Platform & Automation Engineer to own and scale our enterprise AI platform capabilities. This role will serve as the primary owner of the IBM watsonx platform and Google Cloud Vertex AI platform , while providing support to Azure driving adoption, standardization, automation, and governance across the organization. The role also includes leading a team responsible for day‑to‑day AI model and application onboarding, pipeline automation, DevSecOps integration, BI tooling, and AI governance—including maintenance of IBM watsonx.governance and vertex AI.

This is a high‑impact position suited for a technically strong leader who can lead technical team, architect solutions, scale platforms, and align multiple teams across engineering, data science, and business domains.

Key Responsibilities

Platform Leadership

• Serve as the lead owner of IBM watsonx and Google Vertex AI platforms , overseeing configuration, governance, and operational maturity.
• Drive platform onboarding strategy, enablement, and hands‑on support across data science, engineering, and analytics teams.
• Standardize reusable frameworks, templates, and infrastructure patterns for both platforms to accelerate project delivery.

AI & ML Pipeline Automation

• Architect and manage enterprise‑wide CI/CD and MLOps pipelines for:
• Model training, tuning, evaluation, and deployment
• Data ingestion, transformation, and streaming
• Infrastructure provisioning and teardown (IaC)
• Build and maintain reusable templates for AI applications, workflows, and serving endpoints in IBM watsonx.ai and Vertex AI.

Agentic AI Enablement

• Design and operationalize pipelines for Agentic AI systems using LLMs, orchestration agents, and decision engines.
• Integrate intelligent agent workflows with platform capabilities and monitor lifecycle behavior and governance adherence.

AI Governance (incl. watsonx.governance)

• Implement and operationalize AI governance frameworks using IBM watsonx.governance .
• Define model approval workflows, track metadata, enforce responsible AI policies, and ensure transparency, bias detection, and explainability.
• Collaborate with legal, compliance, and information security teams to embed AI governance across all AI/ML systems.

DevSecOps & Automation

• Integrate DevSecOps practices into pipelines—automating vulnerability scans, access policies, and secrets management.
• Embed security compliance and quality gates into all CI/CD workflows across AI and application domains.

Business Intelligence & Semantic Modeling

• Provide architectural guidance to BI teams using Power BI and Looker .
• Oversee data modeling, semantic layer standardization, and connectivity to enterprise data lakes and warehouses.

Team Leadership

• Lead and mentor a cross-functional team of AI platform engineers, MLOps practitioners, BI analysts, and DevSecOps engineers.
• Define goals, delivery milestones, documentation standards, and best practices for scalable operations.

Qualifications

Education

• Bachelor’s or master’s in computer science, Engineering, or related technical field.

Experience

• 8+ years in cloud engineering, MLOps, or platform leadership roles.
• 3+ years leading enterprise platform delivery and infrastructure automation.
• Proven experience managing IBM watsonx and Vertex AI in production environments.
• Hands‑on delivery of secure, automated pipelines using Terraform, GitOps, and containerized workflows.
• Experience implementing AI governance and compliance using commercial tools and internal frameworks.
• Familiarity with BI tools (Power BI, Looker) and semantic modeling techniques.

Technical Skills

• Platforms: IBM watsonx.ai, watsonx.governance, Vertex AI, Azure ML
• Automation: Terraform, Ansible, GitHub Actions, GitLab CI, Azure DevOps
• Languages: Python, Bash, YAML
• Containers: Docker, Kubernetes
• ML Tools: MLflow, TFX, or similar
• Governance: Bias detection, metadata tracking, model lineage, risk management

Preferred Qualifications

• Certifications: GCP, IBM, or Azure AI/MLOps certifications
• Experience with Agentic AI systems (e.g., LangChain, IBM Orchestrate, or custom frameworks)
• Familiarity with NIST, EU AI Act, or internal model risk governance frameworks
• Prior experience deploying internal platform-as-a-service offerings for AI/ML

Employee Type:

Permanent

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