AI Platform Architect

Tata Consultancy Services; Minneapolis (MN); On-site; USD 90,000 - 110,000; Full time

Job summary

Tata Consultancy Services is seeking an AI Platform Architect to design and implement enterprise AI/ML solutions. The role emphasizes LLMs, prompt engineering, RAG, agent workflows, embeddings and vector databases, with cloud knowledge across Azure, AWS or GCP. Expect strong Python skills, DevOps, MLOps, and governance focus.

Salary range is $90,000–$110,000 per year, with emphasis on secure, scalable architectures across multi-cloud/hybrid/on-prem environments and production readiness.

Qualifications

• 3+ years hands-on AI/ML or Generative AI architecture in enterprise environments.
• Strong experience with LLMs, prompt engineering, RAG, agent workflows, embeddings, vector databases and API-based AI services.
• Cloud architecture across Azure, AWS or GCP; microservices, APIs, distributed/event-driven systems.
• Proficiency in Python, modern AI frameworks, DevOps, MLOps/LLMOps, CI/CD and automation.
• Knowledge of AI governance, model risk management, guardrails and adversarial testing.
• Experience integrating AI into ITSM, observability, knowledge systems and regulated environments.
• Define end-to-end architecture for enterprise AI solutions including LLM apps and model orchestration.
• Design secure, scalable AI blueprints across cloud, hybrid and on-prem environments.
• Architect prompt orchestration, embeddings, vector DB integrations and traceability.
• Embed security-by-design and responsible AI controls (IAM, API protection, logging, monitoring).
• Define MLOps/LLMOps, CI/CD, deployment, observability and production readiness.

Responsibilities

• Define end-to-end architecture for enterprise AI solutions including LLM-based applications, RAG, agentic workflows and model orchestration services.
• Design secure, scalable, maintainable and cost-effective AI blueprints across cloud, hybrid and on-premises environments.
• Architect prompt orchestration, contextual grounding, embeddings, vector database integration, retrieval quality and guardrails.
• Embed security-by-design and responsible AI controls covering IAM, API protection, auditability, logging and monitoring.
• Define MLOps/LLMOps, CI/CD, deployment, observability, evaluation framework and production readiness checklist.

Tools

Python

Job description

Job Description

AI Platform Architect

3+ years hands-on experience designing and implementing AI/ML or Generative AI solutions in enterprise environments.

Strong experience with LLMs, prompt engineering, RAG, agent workflows, embeddings, vector databases and API-based AI services.

Strong cloud architecture knowledge across Azure, AWS or GCP, plus microservices, APIs, distributed systems and event-driven architecture.

Experience with Python, modern AI/ML frameworks, DevOps, MLOps/LLMOps, CI/CD, infrastructure automation, documentation and architecture governance.

Familiarity with AI governance, model risk management, responsible AI standards, security reviews, red teaming, guardrails and adversarial testing.

Experience integrating AI into ITSM, observability, knowledge systems, workflow engines and regulated enterprise environments.

Define end-to-end architecture for enterprise AI solutions including LLM-based applications, RAG, agentic workflows and model orchestration services.

Design secure, scalable, maintainable and cost-effective AI blueprints across cloud, hybrid and on-premises environments.

Architect prompt orchestration, contextual grounding, embeddings, vector database integration, retrieval quality, hallucination controls and traceability.

Embed security-by-design and responsible AI controls covering IAM, API protection, auditability, logging, monitoring, data leakage and prompt injection mitigation.

Define MLOps/LLMOps, CI/CD, deployment, observability, evaluation framework, production readiness checklist and reusable AI reference architectures.

Salary Range- $90,000-$110,000 a year