Role: Sr. Specialty Software Engineer – GenAI Engineer / Agentic AI Engineer
Contract Type: [W2 Contract]
Industry: Direct client, Banking domain
Location: Concord, CA Hybrid
Work Arrangement: Hybrid – 3 days onsite (Monday, Wednesday, Thursday preferred)
Contract: 12+ months, with potential extension
Position Overview
We are seeking a hands-on Specialty Software Engineer with strong Python development skills and practical experience in Generative AI / Agentic AI to join a high-visibility Marketing Technology (MarTech) initiative.
The team is building a greenfield Agentic AI platform designed to enable personalized customer offers and intelligent campaign orchestration. The platform will leverage multiple specialized AI agents that work together to determine customer eligibility, select appropriate offers, determine when offers should be presented, and orchestrate campaign workflows.
This is a hands-on engineering role focused on building new AI capabilities and taking them toward production. The ideal candidate is a strong Python engineer first, with practical GenAI/LLM and Agentic AI experience layered on top.
Key Responsibilities
- Design, develop, and maintain production-quality Python services and components supporting AI/agent workflows.
- Build and enhance LLM-powered AI agents for business and customer engagement use cases.
- Develop and integrate multi-agent workflows, including agent-to-agent communication and orchestration.
- Design reusabhi le and scalable components for agent lifecycle management, coordination, and execution.
- Integrate LLM capabilities through APIs and internal AI platforms.
- Apply prompt engineering techniques to improve agent accuracy, reliability, and task execution.
- Work with vector databases and knowledge retrieval technologies to support RAG and agent-based applications.
- Structure and organize data into effective knowledge layers/knowledge structures that can support LLM and agent workflows.
- Implement AI guardrails and controls to ensure reliable, safe, and controlled agent execution.
- Connect AI agents with backend services, data sources, workflows, and other enterprise systems.
- Troubleshoot complex technical issues and independently make sound engineering decisions.
- Evaluate AI-generated code and ensure that solutions meet production-quality engineering standards.
- Leverage modern AI-assisted development tools such as Claude and similar tools while maintaining strong ownership of code quality and technical decisions.
- Collaborate with engineering, data, product, and business teams to develop new AI-driven use cases.
- Help move prototypes and agent capabilities from development into production-ready solutions.
Required Skills & Experience
Must Have
- Strong hands-on Python development experience with the ability to write, understand, debug, and troubleshoot production code.
- Practical experience developing Generative AI / LLM-based applications.
- Hands-on experience building or contributing to AI agents / Agentic AI solutions.
- Understanding of agent orchestration, agent workflows, and multi-agent architectures.
- Experience integrating LLMs through APIs or AI platforms.
- Strong understanding of prompt engineering and LLM application development.
- Experience with vector databases and semantic retrieval.
- Understanding of RAG/knowledge retrieval concepts and how data supports LLM applications.
- Experience implementing or understanding AI guardrails, controls, and responsible AI practices.
- Strong problem-solving, debugging, system design, and software engineering skills.
Preferred Skills
- Experience building multi-agent systems or agent-to-agent communication.
- Experience with knowledge graphs, knowledge layers, or structured knowledge systems.
- Experience with workflow orchestration and event-driven architectures.
- Experience deploying AI applications on OpenShift/OCP, Google Cloud Platform, AWS, Azure, or other cloud platforms.
- Experience with Agentic AI frameworks such as LangGraph, LangChain, Google ADK, AutoGen, CrewAI, or similar.
- Experience with vector technologies such as Pinecone, FAISS, Weaviate, Chroma, Milvus, or similar.
- Experience working in Marketing Technology, campaign orchestration, customer engagement, or financial services.
- Familiarity with modern AI-assisted software development tools such as Claude, GitHub Copilot, or similar.
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