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: www.incubit.com
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.