AI Solution Architect

AI Solution Architect

Experience: 4 to 7 years

IMMEDIATE Joinners will be given a high Priority.

Work Mode: Office(5 Days)

Location: Hyderabad ( Hi-Tech City)

Job Description

Own the end to end architecture for AI solutions and take them from prototype into production. Design how models, data pipelines, applications, and cloud infrastructure fit together, then stay hands-on through deployment, monitoring, and scale.

Tech Stack

Python, LLMs and agent frameworks (Google ADK, LangGraph, LangChain), RAG, Vertex AI, GCP (GKE, Cloud Run, BigQuery, Pub/Sub, Cloud Storage), MLOps tooling, Docker, Kubernetes, Terraform, FastAPI, REST APIs, SQL, Vector databases, CI/CD

Requirements

• B.E./B.Tech/M.Tech in CS, IT, Data Science, or related field
• 4 to 7 years in software or AI engineering, with ownership of architecture for systems that reached production
• Proven record of taking at least one AI or ML project into live production use
• Strong Python, plus one other production language
• LLM application patterns: RAG, agents, tool calling, prompt engineering, evaluation harnesses
• MLOps practice: model and prompt versioning, automated evaluation, staged rollout, rollback, retraining triggers
• Model serving design across batch, real time, and streaming inference, with scaling and cost controls
• Cloud deployment experience, GCP preferred (Vertex AI, GKE, Cloud Run, BigQuery)
• API, microservice, and event-driven architecture design
• Data engineering fundamentals: pipelines, warehousing, data quality
• Security, access control, and data privacy as applied to AI systems
• Strong communication and documentation, able to defend a design decision with reasoning

Good to Have

• Google Cloud Professional Machine Learning Engineer or Professional Cloud Architect certification
• Experience with Gemini Enterprise and building agents in Gemini Enterprise
• Inference optimisation: quantisation, distillation, caching, batching, cost reduction
• Vector DB experience at scale (Vertex AI Vector Search, Pinecone, Qdrant, pgvector)
• Responsible AI controls: guardrails, human in the loop review, bias checks, auditability
• Domain exposure in government, public sector, education, agriculture, or law enforcement technology
• Experience leading a small team of engineers
• Open source contributions, publications, or conference talks in the AI space.

Please share your updated CV along with below details:

Current CTC:

Expected CTC:

Notice Period: