AI Solution Architect

Role overview

AI Solution Architect at Techjays

Required qualifications

• 8+ Years Own the end-to-end solutioning process - from understanding client requirements to designing architectures that are technically sound and commercially viable.
• Partner with pre-sales and business development to respond to RFPs, build proposals, create solution decks, and lead client presentations and discovery calls.
• Conduct architecture reviews and technical assessments for ongoing projects, ensuring solutions align with best practices, scalability, security, and client expectations.
• Translate complex business problems into clear, structured technical solutions spanning AI, cloud, backend systems, and integrations.
• Define high-level and low-level architecture for AI-native applications, including LLM integrations, RAG pipelines, agentic workflows, MCP-based tool/agent integrations, and enterprise data platforms.
• Act as a technical advisor to clients during pre-sales and early delivery phases, building confidence and trust through clarity and expertise.
• Collaborate with engineering teams to ensure smooth handoff from solutioning to execution, maintaining architecture integrity throughout delivery.
• Evaluate build-vs-buy and model/provider trade-offs (LLMs, vector databases, orchestration frameworks) to recommend the right AI stack for each client's needs.
• Stay current with emerging AI technologies, cloud platforms, and enterprise architecture trends to bring relevant, forward-thinking solutions to clients.
• Strong foundation in backend engineering - Python, REST APIs, microservices, and distributed systems.
• Hands-on experience with cloud platforms (AWS, Azure, or GCP), CI/CD, Docker, and Kubernetes.
• Deep understanding of AI-native solution design - LLM integrations, RAG pipelines, AI agents and agentic workflows, MCP (Model Context Protocol), vector databases, prompt engineering, and multi-agent orchestration.
• Familiarity with LLMOps practices - model evaluation, observability, cost/latency optimization, and responsible-AI/governance considerations.
• Experience with enterprise databases, data architecture, and integration patterns.
• Proven ability to create solution documents, architecture diagrams, and proposal decks that are clear and client-ready.
• Strong grasp of security, scalability, and compliance considerations in enterprise systems.

Employment details

• Location: Coimbatore [India]