Senior AI Platform Engineer

Tata Consultancy Services Limited; Oaks (PA); On-site; USD 110,000 - 130,000; Full time

Benefits offered by this job

Discretionary annual incentive

Comprehensive medical coverage

Parental leaves

Auto & home insurance

Certification & training reimbursement

Time off & holidays

Job summary

Tata Consultancy Services Limited in Oaks, PA, is seeking an experienced AI/ML platform engineer to design and operate enterprise-grade GenAI and LLM infrastructure. You will build scalable cloud-native and on-prem solutions, deploy model endpoints, and enable robust MLOps practices.

The role demands deep Kubernetes experience, Python programming, and hands-on work with cloud providers (AWS/Azure). Collaboration with security and data teams is essential.

Qualifications

• Strong cloud engineering and AI/ML platform experience.
• Kubernetes, containers, IaC, CI/CD, and API technologies.
• Proficiency in Python; Go/C++/Rust a plus.
• Experience with ML/LLM deployment and GenAI frameworks.
• Knowledge of vector databases, embeddings, model APIs, and AI orchestration.
• Experience with monitoring, telemetry, security, and production support.
• Hands-on Kubernetes, Docker, and cloud platforms (AWS/Azure).
• Familiarity with LangChain, LangGraph, Ray, Kubeflow; IaC tools Terraform/Ansible.

Responsibilities

• Build and maintain enterprise AI/ML and GenAI platform capabilities.
• Implement model endpoints, gateways, orchestration layers, and AI services.
• Develop infrastructure for LLMs/SLMs/RAG/embeddings and AI agents.
• Create automated deployment and CI/CD pipelines for AI apps and models.
• Enable MLOps/LLMOps: deployment, monitoring, versioning, observability.
• Support model routing, inference management, and cost optimization.
• Integrate AI platforms with enterprise security, logging, and networking.
• Automate infrastructure provisioning and platform configuration.
• Collaborate with AI architects, data engineers, and security teams.

Skills

Cloud engineering

AI/ML platform engineering

Python

Go/C++/Rust (optional)

Kubernetes

CI/CD

API technologies

ML/LLM deployment

AI orchestration

Education

Bachelor of Computer Science

Tools

Kubernetes

OpenShift

AWS

Azure

Terraform

Ansible

LangChain / Kubeflow

Job description

Job Description

Must Have Technical/Functional Skills

• Strong cloud engineering and AI/ML platform engineering experience.
• Kubernetes, containers, Infrastructure as Code, CI/CD, and API technologies.
• Python and software engineering experience.
• Experience with ML/LLM deployment and GenAI frameworks.
• Knowledge of vector databases, embedding models, model APIs, and AI orchestration.
• Experience with monitoring, telemetry, security, and production support.
• Programming: Advanced proficiency in Python; additional experience in Go, C++, or Rust is often preferred.
• Infrastructure & Cloud: Hands-on expertise with Kubernetes, Docker, and cloud platforms like AWS (SageMaker, Bedrock) or Azure (AI Foundry, OpenAI).
• AI Frameworks: Familiarity with orchestration and LLM tooling such as LangChain, LangGraph, Ray, or Kubeflow.
• Infrastructure-as-Code (IaC): Knowledge of automation tools like Terraform and Ansible.

Roles & Responsibilities

• Build and maintain enterprise AI/ML and GenAI platform capabilities.
• Implement model endpoints, gateways, orchestration layers, and AI services.
• Build infrastructure supporting LLMs, SLMs, RAG, embeddings, vector stores, and AI agents.
• Develop automated deployment and CI/CD pipelines for AI applications and models.
• Implement LLMOps/MLOps capabilities covering deployment, monitoring, evaluation, versioning, and observability.
• Implement model-routing and inference-management capabilities.
• Support token, compute, latency, and inference-cost optimization.
• Integrate AI platforms with enterprise identity, security, logging, monitoring, networking, and API-management services.
• Automate infrastructure provisioning and platform configuration.
• Establish production reliability, scalability, resilience, and operational standards.
• Partner with AI architects, application engineers, data engineers, and security teams.
• Platform Architecture: Design and deploy scalable, cloud-native or bare-metal infrastructure (using Kubernetes, OpenShift, or AWS/Azure) to support large language models (LLMs) and machine learning workloads.
• Model Operations (MLOps/LLMOps): Optimize model serving, inference performance, GPU utilization, and automated pipelines for fine-tuning and deploying AI models.
• Agentic & GenAI Integration: Build and maintain shared services like AI gateways, Retrieval-Augmented Generation (RAG) frameworks, and autonomous agent orchestration platforms.
• Governance & Security: Enforce enterprise data protection, compliance, auditability, and cybersecurity standards across all AI tooling.
• Developer Enablement: Create self-service platforms, APIs, and monitoring/observability tools so internal software and data science teams can safely adopt AI capabilities.

TCS Employee Benefits Summary

• Discretionary Annual Incentive.
• Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans.
• Family Support: Maternal & Parental Leaves.
• Insurance Options: Auto & Home Insurance, Identity Theft Protection.
• Convenience & Professional Growth: Commuter Benefits & Certification & Training Reimburseme nt.
• Time Off: Vacation, Time Off, Sick Leave & Holidays.
• Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.

Qualifications

BACHELOR OF COMPUTER SCIENCE

Salary Range $110,000 - $130,000 a year