Solution Architect - Agentic AI & Data

Location: Any US (preferred metro areas: San Francisco Bay Area, Seattle, New York / New Jersey, Atlanta, Chicago, Dallas)

About the role

The Agentic AI Architect is a client-facing consulting role within TCS’s AI & Data business unit in the Americas. You will design next-generation AI solutions that leverage autonomous “agentic” AI systems—systems that make decisions, take actions, adapt to changing environments, and continuously learn. TCS anticipates a shift from traditional chatbots to multi-agent AI frameworks where multiple agents collaborate to determine actions. This role involves shaping AI architecture across industries such as BFSI, Manufacturing, Life Sciences, Telecom, Retail, Travel, and Consumer Goods, delivering vertical-specific solutions and driving thought leadership in emerging business units.

Responsibilities

• Lead end-to-end AI architecture design for systems incorporating autonomous agents and LLM-based components, ensuring alignment with business goals.
• Conduct client workshops to understand business requirements and translate them into AI architecture blueprints.
• Design frameworks for multi-agent systems, defining agent roles, communication protocols, and fail-safes.
• Outline integration with existing enterprise ecosystems, ensuring scalability and resilience.
• Incorporate advanced prompt engineering techniques and retrieval-augmented generation (RAG) into solution design.
• Guide engineering teams through prototyping and solution delivery, troubleshooting high-level architectural issues.
• Customize architectural decisions to industry-specific requirements, balancing reusability with necessary adaptations.
• Continuously evaluate new tools and methodologies, integrating them into architecture standards.
• Engage with client technology leaders, presenting architectural proposals and reviewing technical designs; travel as required.
• Ensure ethical AI and safety considerations are embedded from the architecture stage, documenting and mitigating potential risks.

Requirements

• Extensive experience in designing and architecting AI or machine learning solutions in an enterprise context.
• Deep technical knowledge of machine learning and AI techniques, especially Generative AI and large language models.
• Knowledge of multi-agent system patterns and frameworks.
• Ability to craft effective prompts and chaining strategies for LLMs; familiarity with retrieval-augmented generation methods.
• Strong grasp of AI ethics and safety principles, able to identify ethical risks and design mitigations.
• Deep understanding of cloud architecture and distributed system design (AWS, Azure, GCP).
• Solid understanding of data architecture as it relates to AI, including data pipelines, databases, and data lakes.
• Excellent communication and stakeholder management skills; capable of leading discussions with C-level executives and technical teams.
• Prior consulting or client-facing experience, adept at requirement gathering and crafting proposals.
• Creative mindset to devise innovative solutions leveraging AI agents; strong problem-solving skills.
• Demonstrated habit of continuous learning, staying updated via research papers, conferences, or hands-on experimentation.

Skills

• AI & ML Frameworks: OpenAI GPT models, Google PaLM/Vertex AI, Hugging Face Transformers library.
• SaaS AI & Data Platforms: Experience with platforms for agentic AI development, implementation, orchestration, and AI guardrails.
• Agentic AI Tooling: LangChain, Microsoft’s Semantic Kernel.
• Retrieval Systems: Vector databases, semantic search.
• Cloud Services: Cloud AI services, serverless computing, containerization, DevOps tools.
• Programming & Scripting: Proficiency in Python and at least one general-purpose language.
• Data Platforms: Relational databases, NoSQL stores, data processing frameworks.
• Integration & APIs: Designing and using APIs, event-driven architectures, message brokers.
• DevOps & MLOps: CI/CD pipelines, infrastructure as code, MLOps principles and tools.
• Security & Compliance Tools: Identity and access management, encryption, compliance tools.
• Collaboration & Design: UML design tools, agile project management tools.
• Emerging Tech: Knowledge graphs, reinforcement learning frameworks.

Qualifications

• Bachelor’s degree in Computer Science or related field.

Pay

$155,550 – $247,250 a year