TrnDigital
Website:
trndigital.com
Job details:
AI Architect
Location: Remote, India
Employment Type: Full-Time
Experience: 8+ years overall, including 3+ years in AI/ML and GenAI solution architecture
About the Role
TrnDigital is looking for an experienced AI Architect to lead the architecture and delivery of enterprise-grade AI and Generative AI solutions.
This is a hands-on, client-facing role for someone who can take ownership from solution conception through production deployment. You will work directly with customers to understand business requirements, define the technical approach, support presales and solutioning, and provide technical leadership to development teams.
We are looking for someone who combines strong architecture skills with hands-on AI engineering experience and can confidently engage with both technical teams and senior customer stakeholders.
Key Responsibilities
- Architect end-to-end enterprise AI and GenAI solutions, including RAG, Agentic AI, conversational AI, intelligent document processing, and structured data extraction.
- Design solutions using Microsoft Foundry, Azure AI Search, Azure Document Intelligence, LangChain, LangGraph, and LangSmith.
- Work directly with customers to understand business requirements and translate them into scalable, secure, and production-ready architectures.
- Lead technical discovery sessions, architecture discussions, solution walkthroughs, and customer presentations.
- Support presales activities, including solution design, estimations, RFP responses, technical proposals, demonstrations, and PoCs.
- Define architecture patterns, development standards, integration approaches, and engineering best practices.
- Provide technical leadership and mentoring to AI developers and engineers.
- Conduct architecture and code reviews and ensure solutions meet enterprise security, scalability, performance, and maintainability requirements.
- Design and review APIs and integration layers using Python, FastAPI, REST APIs, and OpenAPI/Swagger.
- Establish approaches for LLM evaluation, observability, tracing, and quality measurement using LangSmith, RAGAS, or equivalent frameworks.
- Work with delivery teams to troubleshoot complex technical challenges and drive solutions through production deployment.
- Contribute to technical hiring and evaluation of AI engineering talent.
Required Skills & Experience
- 8+ years of overall technology experience with at least 3+ years focused on AI/ML, GenAI, or AI solution architecture.
- Strong hands-on development experience with Python.
- Deep understanding of LLMs, RAG architectures, Agentic AI, embeddings, vector/semantic search, and prompt engineering.
- Hands-on experience with LangChain and LangGraph.
- Strong experience with Microsoft Foundry and the Azure AI ecosystem.
- Experience with Azure AI Search and Azure Document Intelligence.
- Experience designing and implementing enterprise-grade APIs using FastAPI and REST.
- Understanding of LLM evaluation and observability using LangSmith, RAGAS, or similar frameworks.
- Experience designing secure, scalable, and production-ready cloud AI solutions.
- Understanding of CI/CD, source control, cloud deployment, monitoring, and enterprise security practices.
- Proven experience in client-facing technical roles, including requirements gathering, architecture discussions, and solution presentations.
- Experience supporting presales, proposals, estimations, RFPs, and PoCs.
- Strong written and verbal communication skills.
Nice to Have
- Experience designing multi-agent and agent orchestration solutions.
- Experience with intelligent document processing and structured extraction from invoices, contracts, reports, tables, and other complex documents.
- Experience building automated document or report generation solutions using AI.
- Exposure to multiple LLM providers and model selection/evaluation strategies.
- Previous experience leading or mentoring AI engineering teams.
- Microsoft Azure or AI certifications.
What We’re Looking For
We are particularly interested in candidates who are architects who still build. You should be comfortable discussing architecture with senior stakeholders and equally comfortable getting into Python, APIs, RAG pipelines, prompts, agents, and implementation details with the engineering team.
This is an opportunity to play a key technical leadership role as we continue to expand our enterprise AI capabilities.
Interested candidates can apply directly through LinkedIn.
Click on Apply to know more.
