About this opportunity
Incubit lists this Agentic AI / MCP Lead Engineer opportunity in town of philadelphia, New York. Review the employer’s description below for duties, qualifications and application requirements.
Job description
Job Title: Agentic AI / MCP Lead Engineer
Location: Philadelphia ,New York, USA
Experience Level:6+ years.
Who Can Apply- US Citizen, Green Card Holder, Valid US Work permit
Company Overview: Incubit LLC is a well-established and innovative technology company based in Ohio, USA. We are seeking a talented Agentic AI / MCP Lead Engineer with expertise in GenAI & MCP to join the project of one of the leading Bank based at New York, USA. Website:
Key Responsibilities
Agentic AI Strategy & Architecture
Define the enterprise architecture for Agentic AI platforms and solutions.
Design autonomous and semi-autonomous agent workflows for customer, employee, and operational use cases.
Establish architectural patterns for multi-agent collaboration, orchestration, planning, reasoning, and execution.
Drive technical vision for AI-powered business transformation initiatives.
Design and implement MCP-based integrations between agents, tools, enterprise systems, and knowledge sources.
Develop reusable MCP servers and connectors for business applications, APIs, databases, and enterprise platforms.
Define standards for tool discovery, context management, permissions, and secure access controls.
Ensure interoperability between AI models, agents, and enterprise ecosystems.
AI Agent Development
Build intelligent agents capable of:
Develop agent memory, context handling, and state management capabilities.
Implement human-in-the-loop controls and agent governance mechanisms.
RAG & Knowledge Systems
Design and implement enterprise RAG solutions.
Integrate structured and unstructured data sources into agent workflows.
Optimize retrieval quality, grounding, relevance ranking, and response accuracy.
Architect integrations with:
CRM, ERP, and payment systems
Knowledge repositories
Search platforms
Build scalable backend services supporting agent operations.
Develop reusable frameworks, SDKs, accelerators, and integration patterns.
Governance, Security & Responsible AI
Define guardrails for AI agents, tool usage, and autonomous actions.
Implement authentication, authorization, auditing, and monitoring controls.
Ensure compliance with enterprise security, privacy, and regulatory requirements.
Establish observability, traceability, and evaluation frameworks.
Performance, Reliability & Optimization
Measure agent effectiveness, latency, cost efficiency, and task completion rates.
Optimize prompts, workflows, retrieval pipelines, and tool interactions.
Implement testing frameworks, evaluation benchmarks, and quality assurance processes.
Improve scalability and resiliency of agent platforms.
Technical Leadership
Lead engineering teams building enterprise AI agent solutions.
Mentor engineers on AI architecture, MCP, agent frameworks, and GenAI best practices.
Collaborate with Product Managers, Architects, Data Scientists, and Business Stakeholders.
Drive technical governance and engineering standards.
Required Skills & Experience
Agentic AI & LLM Engineering
6+ years of software engineering experience with 3+ years in GenAI solutions.
Hands-on experience building AI agents using frameworks such as:
LangGraph
LangChain
Semantic Kernel
AutoGen
CrewAI
OpenAI Agents SDK
Strong understanding of agent planning, reasoning, memory, and orchestration patterns.
MCP & Integration Development
Experience implementing and extending Model Context Protocol (MCP).
Building MCP servers, tool adapters, connectors, and integration layers.
Deep understanding of tool calling, context sharing, and enterprise system integration.
Data & Retrieval Technologies
Embeddings, semantic search, hybrid search, and retrieval optimization
Data pipelines and knowledge engineering
Preferred Qualifications
Exposure to Payments, Banking, Financial Services, or Digital Commerce domains.
Knowledge of workflow orchestration tools such as Airflow, Temporal, or Prefect.
Familiarity with GraphRAG, Knowledge Graphs, and advanced retrieval architectures.
Experience with Azure AI Foundry, OpenAI, Anthropic, Gemini, or multi-model ecosystems.
Enterprise Agentic AI architecture
MCP integration framework and server ecosystem
Multi-agent orchestration platform
RAG and knowledge retrieval architecture
Tool and connector catalog
Security and governance framework
Agent evaluation and monitoring framework
Technical standards and engineering best practices
Production-ready agentic use cases and accelerators
AI platform roadmap with stakeholder approval
Type: Contract
Duration: 6 Month (Extendable)
Working Model: WFO
Hourly Rate: Competitive, based on experience.
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Who can apply
Review the original listing for work authorization, qualifications and employer requirements.