Roles & Responsibilities :

Agentic AI :

- Design agentic systems for enterprise workflows (e.g., vendor payments, onboarding, reconciliation, procurement).

- Implement tools-using agents with Banking, ERP APIs, payment gateways, document systems, and compliance engines.

- Build multi-agent ecosystems (validation, compliance, payment, exception agents).

- Ensure safety, guardrails, auditability, policy enforcement, and RBI AI Governance.

AI/ML Engineering :

- Lead implementation of RAG pipelines, embeddings, vector stores, and retrieval optimizations.

- Evaluate and integrate LLMs (OpenAI, Azure OpenAI, Llama, Claude, Mistral) based on cost, latency, and accuracy.

- Drive model evaluation, prompt engineering, fine-tuning, and performance optimization.

- Implement observability : drift detection, hallucination control, feedback loops.

Enterprise Architect :

- Architect integrations with ERP (SAP/Oracle/Zoho/Tally/Custom), banking APIs, identity systems, and workflow engines.

- Define API contracts, event schemas, and integration governance.

- Ensure security, IAM, encryption, and compliance (SOC2, ISO, RBI, and GDPR).

- Build tools and re-usable libraries for enterprise-class architecture.

Core Technical Skills :

- Expertise in AI/LLM systems, RAG, vector DBs.

- Experience with agentic frameworks (AutoGen, LangGraph, CrewAI, Semantic Kernel).

- Cloud architecture (Azure/AWS/GCP) - compute, networking, security, serverless.

- Microservices, API gateways, Kafka/EventBridge/PubSub.

- Databases : SQL, NoSQL, graph, vector.

- DevOps : CI/CD, containers, Kubernetes, IaC (Terraform/Bicep).

- Security : OAuth2, JWT, SSO, Zero Trust, data governance.

Banking Domain Expertise :

- Deep experience in designing and implementing banking solutions including Core Banking Applications.

- Understanding of functionality like NPA, AML, ALM, WMS, and Fraud Detection.

- Knowledge of data source structures for analytics (KPIs) and security needs of banking solutions.

Leadership Skills :

- Act as a teacher and evangelist within the company.

- Present technical notes through PPT/videos and maintain a learning library.

- Engage with CIO and CTO level executives.

Selection Process :

- Must present at least two solutions worked on (architecture, design, interoperability), one of which must be in the AI area.

Education :

- Bachelor's / Master's degree in a related field.