Sr. Agentic AI Engineer
Location: Plano, TX / Purchase, NY / Chicago, IL
Work Arrangement: Hybrid
Employment Type: Long-Term Contract
Experience: 8+ Years
Job Summary
We are seeking an experienced Sr. Agentic AI Engineer to design, develop, deploy, and optimize AI agents and Generative AI solutions across enterprise business domains.
The ideal candidate will have strong hands-on experience in software engineering, Generative AI, Agentic AI, AI/ML, and cloud deployment. This role will focus on taking AI agent solutions from prototyping and experimentation through production, while ensuring scalability, reliability, observability, and performance.
The engineer will work closely with business stakeholders, transformation teams, Data Science, Engineering, IT, Digital Product, and AI Platform teams to translate business challenges into scalable AI-powered solutions.
Key Responsibilities
Agentic AI & Generative AI Development
- Design, prototype, develop, test, and deploy domain-specific AI agents.
- Build AI agents capable of performing tasks such as information gathering, reasoning, insight generation, decision support, and intelligent actions.
- Develop multi-agent solutions where AI agents communicate and collaborate to complete complex workflows.
- Develop and execute Generative AI and Agentic AI roadmaps aligned with business and transformation objectives.
- Continuously improve agent performance, reliability, accuracy, and scalability.
- Evaluate emerging GenAI, LLM, and Agentic AI technologies and incorporate relevant capabilities into enterprise solutions.
Software Engineering & AI Development
- Lead AI projects with strong hands-on involvement in software development and coding.
- Develop high-quality, scalable, and maintainable AI applications and services.
- Write and optimize code for AI/ML workloads and production applications.
- Apply software engineering best practices including version control, testing, debugging, code reviews, and CI/CD.
- Translate business requirements and challenges into practical AI-powered technical solutions.
AI Frameworks & Agent Development
- Build solutions using modern Agentic AI frameworks and protocols, including:
- LangChain
- CrewAI
- MCP (Model Context Protocol)
- A2A (Agent-to-Agent)
- Develop agent workflows incorporating LLMs, tools, APIs, memory, retrieval, and orchestration.
- Integrate AI agents with enterprise applications, data sources, APIs, and business workflows.
- Implement appropriate evaluation and validation strategies to ensure reliable AI outcomes.
Cloud Deployment & Integration
- Deploy and operate AI agents and AI services across AWS, Azure, or Google Cloud Platform.
- Design scalable cloud architectures for AI workloads.
- Monitor and optimize AI applications for performance, availability, scalability, and cost efficiency.
- Implement appropriate observability and monitoring across AI agent workflows.
- Integrate AI solutions with existing enterprise platforms and services.
Testing, Validation & Optimization
- Conduct comprehensive testing and validation of AI agents and GenAI solutions.
- Evaluate accuracy, reliability, performance, scalability, and response quality.
- Identify and resolve issues related to AI model performance and application behavior.
- Continuously iterate on AI agents based on testing results, business feedback, and production metrics.
- Establish appropriate safeguards and validation mechanisms for enterprise AI solutions.
Collaboration & Stakeholder Engagement
- Collaborate with business stakeholders and transformation teams to understand business requirements and identify high-value AI use cases.
- Partner with AI Platform, Data Science, Engineering, IT, Digital Product, and business teams to deliver enterprise AI solutions.
- Explain complex AI and technical concepts clearly to technical and non-technical stakeholders.
- Provide technical guidance and contribute to AI architecture and solution design discussions.
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical field.
- 8+ years of professional experience in software development, machine learning, data science, AI engineering, or a related field.
- Proven experience leading AI/ML or Generative AI projects with strong hands-on software development experience.
- Strong proficiency in Python, Java, C++, or similar programming languages, with Python strongly preferred.
- Hands-on experience designing and developing AI agents and Agentic AI solutions.
- Experience with modern Agentic AI frameworks such as LangChain, CrewAI, MCP, A2A, or equivalent technologies.
- Strong understanding of Generative AI, LLMs, AI agent architectures, and AI/ML technologies.
- Experience deploying AI solutions on AWS, Azure, or Google Cloud Platform.
- Strong software engineering, analytical, problem-solving, and debugging skills.
- Ability to work effectively in a cross-functional and collaborative environment.
- Strong communication skills with the ability to explain complex technical concepts to business stakeholders.
Preferred Qualifications
- Experience developing multi-agent architectures and agent orchestration workflows.
- Experience with LLM APIs, prompt engineering, RAG, vector databases, embeddings, and semantic search.
- Experience integrating AI agents with enterprise APIs, applications, and data platforms.
- Experience with AI evaluation, observability, monitoring, and responsible AI practices.
- Experience with Docker, Kubernetes, CI/CD, Git, and cloud-native application development.
- Experience building production-grade AI applications at enterprise scale.
- Experience working with large datasets and complex enterprise environments.
- Experience driving AI transformation initiatives across multiple business domains.
Technical Skills
Programming: Python, Java, C++, Software Engineering
Generative AI: LLMs, Generative AI, Prompt Engineering, LLM APIs
Agentic AI: LangChain, CrewAI, MCP, A2A, AI Agents, Multi-Agent Systems, Agent Orchestration
AI/ML: Machine Learning, AI Model Integration, AI Evaluation, Model Optimization
Cloud: AWS, Azure, Google Cloud Platform
Integration: REST APIs, Enterprise APIs, Data Integration, Application Integration
DevOps: Git, CI/CD, Docker, Kubernetes, Cloud Deployment
Preferred: RAG, Vector Databases, Embeddings, Semantic Search, AI Observability
Key Competencies
- Agentic AI Engineering
- Generative AI & LLM Development
- AI Agent Architecture
- Multi-Agent Systems
- Software Engineering
- Cloud AI Deployment
- AI Solution Design
- AI/ML Integration
- Production AI Development
- Testing & Validation
- Performance Optimization
- Cross-Functional Collaboration
- Technical Problem Solving
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