Senior AI Engineer - Generative AI

About the Role :

We are building AI, Agents, and Agentic AI capabilities to drive measurable business outcomes across functions such as customer acquisition, servicing, collections, risk, operations, productivity, compliance, and internal knowledge workflows.

We are looking for an AI Engineer to develop and implement enterprise-grade AI applications, multi-agent workflows, and GenAI platforms. This role is ideal for a strong hands-on engineer who combines software engineering discipline, LLM / GenAI expertise, agent orchestration knowledge, and production deployment experience.

The person in this role will translate business use cases into scalable AI solutions, implement engineering standards for AI application development, and work closely with data, platform, product, risk, security, and business teams to operationalize AI across the organization.

Role Purpose :

The AI Engineer will be responsible for :

• Designing, building, and maintaining production-grade AI applications and agentic systems

• Implementing LLM-based copilots, AI assistants, retrieval-augmented generation (RAG), workflow agents, and autonomous / semi-autonomous agentic use cases

• Utilizing and improving reusable AI engineering patterns

• Following and promoting best practices across prompt engineering, evaluation, guardrails, observability, deployment, and AI application lifecycle management

• Collaborating with cross-functional teams to execute enterprise AI initiatives

Key Responsibilities :A. AI / GenAI Solution Design & Delivery:

• Build, test, and deploy AI, GenAI, and agentic AI solutions for business use cases

• Implement end-to-end AI solution architectures including the user interaction layer, orchestration / agent framework, LLM inference layer, retrieval layer, memory / context layer, tool / API integration layer, and the monitoring, evaluation, and governance layers

• Develop solutions such as enterprise copilots, internal knowledge assistants, customer support assistants, collections / operations copilots, underwriting / risk / servicing workflow assistants, document intelligence and automated review systems, and agentic workflows for process automation and decision support

B. Agentic AI Architecture & Orchestration:

• Implement single-agent and multi-agent systems for enterprise workflows

• Build agentic patterns such as planner-executor agents, router agents, tool-using agents, workflow agents, retrieval-augmented agents, human-in-the-loop approval flows, and supervisor / specialist multi-agent systems

• Integrate agents with enterprise APIs and microservices, internal knowledge bases, structured and unstructured data, workflow engines, and business rules