Role : Solution Architect

Experience - 10 + Years

NP - Within 30 Days

Location - Mumbai (Goregaon)

Key Skills : Solution Architect, AIML, Rag, LLM, NLP, deep learning, Agentic AI , Gen AI Kubernetes, Docker, CICD, GCP/Azure/AWS

Job Description :

- Presales Leadership : Drive end-to-end RFP/RFI responses, with a strong focus on BFSI and Gen AI/Agentic AI/ML solutioning. Your experience in improving deal win rates through strategic positioning and crafting compelling value propositions will be key.

- AI/GenAI Solutions : Lead the development and delivery of AI-powered solutions, particularly focusing on Generative AI and Agentic AI applications for banking and financial services.

- Consultative Selling & Solution Consulting : Engage with senior client stakeholders, positioning innovative solutions for digital transformation, risk management, and compliance automation across sectors like BFSI, InsurTech, and Healthcare.

- Thought Leadership & GTM : Develop and communicate thought leadership around AI/GenAI in BFSI. Lead the go-to-market (GTM) strategy and collaborate with sales teams to win new business.

- Innovation & Client Engagement : Leverage your expertise in developing POCs, demos, and tailored GTM approaches to showcase cutting-edge AI solutions and drive client success.

Qualifications :

- 15+ years of experience in AI solutions, presales, and consulting across BFSI and other key industries.

- Expertise in BFSI, AI/GenAI, and RFP/RFI management.

- Proven success in driving digital transformation, crafting strategic solution offerings, and leading large-scale client engagements.

Technical Skills :

Must Have :

- Prior experience in Architect / Principal / Lead roles is mandatory

- Machine Learning/Deep Learning/NLP/Computer Vision

- Development of Generative AI solutions using GPT, LLaMA, Mistral, Claude or equivalent LLMs

- RAG/Graph-RAG/Embeddings/Vector Databases

- Agentic AI / Multi-Agent frameworks (LangChain, LangGraph, AutoGen, CrewAI or similar)

- Statistical Modeling/Feature Engineering/Model Evaluation etc.

- Strong Hands-On TensorFlow / PyTorch / JAX

- API Integration

- AWS / GCP / Azure (any one mandatory, multi-cloud preferred)

- Docker, Kubernetes

- CI/CD Pipelines, Model Monitoring, Logging, Drift Detection

- Tools SageMaker/Bedrock/VertexAI/MLflow (or equivalents)

- SQL & NoSQL databases

- Kafka / SQS or similar event-driven systems