SENIOR LEAD • GEN AI • AGENTIC AI • SOLUTIONS CONSULTING

Senior Lead – Gen AI Solutions Consultant

Forward Deployed Agentic Engineer

Lead the deployment of production-grade Agentic AI solutions into enterprise operations, translating business processes into intelligent workflows powered by LLMs, MCP, RAG, Python and AI agents.

Experience: 18+ Years

AI Experience: 7+ Years

Domain: Enterprise / Banking

Work Model: On-site

Travel: Up to 10%

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IDEAL CANDIDATE

Who Is This Role For?

This is a senior, hands-on AI engineering and consulting role for professionals who can move beyond AI experimentation and deploy production-grade agentic solutions that create measurable business value.

Forward-Deployed AI Engineer

Comfortable working directly with business and operations teams to move Agentic AI solutions from concept into production.

Agentic AI Architect

Can design multi-step agents with planning, tool calling, orchestration, memory, guardrails and structured outputs.

GenAI Solutions Consultant

Can translate operational problems into AI use cases, define success metrics and communicate technical trade-offs to senior stakeholders.

Enterprise AI Builder

Has strong Python, LLM, RAG and enterprise integration skills with a focus on reliability, governance and measurable outcomes.

ROLE OVERVIEW

From Business Process to Production AI

The role sits at the intersection of business operations, product development and AI engineering. The objective is not simply to build AI prototypes, but to embed intelligent agents into real enterprise workflows and demonstrate measurable value.

Discover Understand business processes

Design Create agentic workflows

Integrate Connect enterprise systems

Deploy Move solutions to production

Measure Track business value

KEY RESPONSIBILITIES

What You Will Do

Deploy Agentic AI Into Live Operations

Lead end-to-end deployment of agentic AI solutions into enterprise workflows for automation and decision support.

Conduct Process Discovery

Analyze SOPs, runbooks, workflows, process-mining outputs, videos and other operational artifacts to identify AI opportunities.

Translate Processes Into Agentic Workflows

Convert complex business processes into reusable AI agent patterns and solution blueprints.

Define Business Value

Establish KPIs and quantify cost reduction, cycle-time improvements, productivity gains and risk mitigation.

Build Multi-Step AI Agents

Develop agents capable of reasoning, tool use, task execution, orchestration and structured output generation.

Implement MCP-Based Integrations

Use Model Context Protocol tools to connect LLMs with enterprise APIs, systems and data sources.

Develop Reusable Agentic Assets

Build reusable agents, workflow components, prompts, tool-use patterns and orchestration blueprints.

Govern the Agent Skills Library

Establish versioning, governance and lifecycle practices for reusable agent capabilities across enterprise use cases.

PROCESS INTELLIGENCE

Discover High-Value AI Opportunities

Process Analysis

Study SOPs, runbooks, workflows, recordings and process-mining outputs to understand how work is actually performed.

Use-Case Identification

Identify repetitive, complex and decision-heavy processes where AI agents can create meaningful operational value.

Value Realization

Establish measurable KPIs and ROI models around productivity, cost, cycle time and risk reduction.

AGENTIC AI ARCHITECTURE

Build Intelligent Multi-Step Workflows

Design agents that can reason over context, select tools, interact with enterprise systems, execute tasks and coordinate across multiple workflow steps.

AI Agents Multi-Agent Systems Tool Calling Function Calling Planning Memory Orchestration Structured Outputs Guardrails Workflow Automation

MCP & ENTERPRISE INTEGRATION

Connect AI to Enterprise Systems

Model Context Protocol

Leverage MCP tools to provide LLM agents with controlled access to enterprise capabilities and information.

Enterprise APIs

Integrate agents with internal services, SaaS applications, databases and operational systems through APIs.

Tool-Augmented AI

Build workflows where AI reasoning is combined with reliable tools to perform real-world actions.

LLM & GENERATIVE AI

Hands-On LLM Expertise

GPT Claude Gemini Prompt Architecture Prompt Engineering Reasoning Chains Constrained Generation Output Validation Model Selection Latency Optimization Cost Optimization

RAG & KNOWLEDGE INTEGRATION

Ground Agent Responses With Enterprise Knowledge

Retrieval-Augmented Generation

Implement RAG pipelines that connect LLMs to trusted enterprise knowledge and operational information.

Retrieval Strategy

Work with document chunking, embeddings, retrieval strategies and re-ranking to improve context quality.

Contextual Grounding

Improve reliability by ensuring AI outputs are grounded in relevant and trustworthy information.

TECHNICAL EXPERTISE

What You Should Know

Python Advanced Python skills for production-grade agentic systems, APIs, state management, async execution and modular services.

LLM Platforms Hands-on experience with modern LLM platforms including GPT, Claude, Gemini or comparable technologies.

Agent Architecture Strong understanding of planning loops, tool calling, memory, multi-agent coordination and guardrails.

RAG & Embeddings Practical experience with embeddings, retrieval, chunking, re-ranking and contextual grounding.

Enterprise Integration Ability to integrate LLM agents with APIs, databases, SaaS tools and internal enterprise services.

AI Evaluation Ability to evaluate model performance, reliability, safety, enterprise readiness and business outcomes.

AGENTIC SKILLS LIBRARY

Build Once. Reuse Everywhere.

Create a governed library of reusable AI capabilities that can be adapted across multiple enterprise and banking use cases.

Task-Specific Agents

Summarization, classification, reconciliation, validation and decision-support agents.

Workflow Components

Data extraction, validation, routing, reasoning chains and enterprise tool integrations.

Prompt & Tool Patterns

Reusable prompt templates, tool-use patterns and orchestration blueprints for consistent delivery.

ENTERPRISE USE CASES

Where Agentic AI Can Create Business Value

Case Resolution Reconciliation Compliance Checks Decision Support Document Processing Workflow Automation Knowledge Assistance Data Validation Operational Intelligence

QUALIFICATIONS

Experience & Leadership Expectations

Industry Experience 18+ years of overall industry experience with 7+ years of Artificial Intelligence Solutions experience.

Production AI Experience designing, deploying and operating production-grade LLM-driven agentic systems.

Customer-Facing Ownership Ability to work directly with customers and senior stakeholders to define AI solutions and success metrics.

Solution Architecture Ability to translate complex business requirements into scalable AI architectures and reusable solution patterns.

Governance Strong focus on reliability, safety, responsible AI, enterprise governance and lifecycle management.

Business Value Ability to quantify ROI and demonstrate measurable operational improvements from AI initiatives.

WORK EXPECTATIONS

Enterprise Delivery Environment

On-Site Work Up to 10% Travel Global Coverage Flexible Shift Timings Enterprise AI Banking Operations Risk & Governance

CORE TECHNOLOGY STACK

Skills & Technologies

Agentic AI Generative AI LLMs GPT Claude Gemini MCP Python RAG Embeddings Vector Search Prompt Engineering Tool Calling Function Calling Workflow Orchestration Multi-Agent Systems Enterprise APIs AI Governance

Build the Future of Enterprise AI

Lead the transformation of complex business processes into production-grade Agentic AI solutions that deliver measurable operational value.

Apply Now ↗