AI Solution Architect
Summary
Technical face of Antino's AI practice: leads pre-sales discovery calls with enterprise clients, designs AI/agentic solutions live with trade-offs and estimates, then stays hands-on building proofs of concept and guiding teams to production. Core stack: Python, FastAPI, LLM platforms (OpenAI, Anthropic, Bedrock), LangGraph/LangChain, vector databases, and AWS/Azure/GCP.
AI Solution Architect
Run the client pre-sales call, design the solution on the spot, and then build it.
The role :
You will be the technical face of Antino's AI practice in front of clients, and also the person who builds what was promised. You will join pre-sales calls with enterprise clients, understand their business problem, and propose a credible AI or agentic solution during the conversation, with trade-offs, risks and a rough effort estimate. After the deal, you stay hands-on. You will build the proof of concept, set the architecture, and guide engineering and data science teams until the solution runs in production.
What you'll do :
- Lead technical discovery calls and workshops with enterprise clients.
- Turn business problems into AI solution designs covering architecture, trade-offs, and risks.
- Own the technical side of RFP and RFI responses, proposals, and SOWs.
- Build agentic systems hands-on : tool-using agents, multi-agent workflows, and integrations.
- Train Antino's internal engineering and data science teams on GenAI and agentic AI practices.
Must-have skills :
- 5+ years in software engineering, data science, or solution architecture, with 2+ years shipping GenAI/LLM solutions to production.
- Proven track record of building agentic AI solutions (tool-calling agents, multi-agent workflows).
- Strong foundations in Python, API development (FastAPI), and classical ML/statistics.
- Experience with LLM platforms (OpenAI, Anthropic, Bedrock) and frameworks (LangGraph, LangChain, LlamaIndex).
- Proficiency in vector databases (Pinecone, Milvus, etc.) and cloud architecture (AWS/Azure/GCP).