We are seeking a Senior GenAI Engineer to help architect and build production-grade GenAI applications, with a strong focus on AI agents, LLM integration, and real-world personalization engines. This role sits within a digital marketing and user experience platform team that is actively deploying AI to enhance both internal productivity and external customer experiences.
The ideal candidate is hands-on, creative, and fluent in LangChain, RAG architectures, and LLM-based application design. You will play a critical role in transforming GenAI concepts into secure, scalable, and observable systems using industry-standard and in-house frameworks. Youll also collaborate with cross-functional teams to ensure safe deployment and long-term stability of AI-driven features.
Key Responsibilities:
Build and deploy GenAI applications using existing LLMs, prompt engineering, and retrieval-augmented generation (RAG).
Architect and orchestrate multi-agent systems, enabling LLM agents to perform workflows and interact across tools/APIs.
Leverage LangChain (required) to build apps that read unstructured data and generate dynamic outputs.
Integrate with custom AI microservices and reference architectures (e.g., blueprint-style systems).
Apply guardrails, safety layers, and observability mechanisms to ensure secure and compliant AI usage (e.g., prompt injection mitigation, logging, and moderation).
Collaborate with product and platform teams to transition projects from POC to full production deployments.
Fine-tune LLMs via prompt optimization; experience with full training pipelines is a plus.
Use Python to build robust, scalable applications and workflows.
We are a company committed to creating inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity employer that believes everyone matters. Qualified candidates will receive consideration for employment opportunities without regard to race, religion, sex, age, marital status, national origin, sexual orientation, citizenship status, disability, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to
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- 610 years of experience in ML/AI engineering, with 23+ years hands-on with GenAI or LLMs.
- Demonstrated experience building GenAI apps that use LLMs and LangChain for prompt chaining and orchestration.
- Experience with RAG (retrieval-augmented generation) for document-based or knowledge-aware use cases.
- Hands-on knowledge of AI agent frameworks, multi-agent orchestration, or self-built agent-like systems.
- Strong understanding of AI safety and compliance, including use of moderation filters, guardrails, and prompt injection protection.
- Fluency in Python for building production-grade AI apps.
- Experience integrating observability and logging into model behavior and system response tracking.
Exposure to frameworks like CrewAI or AutoGen for agent coordination.
Experience with NeMo models, fine-tuning open-source LLMs, or working with hosted models (e.g., Claude, GPT, Falcon).
Knowledge of MCP-style orchestration or blueprint-based AI system design.
Familiarity with basic ML model selection, bias/variance tradeoffs, or working with MongoDB for analytics.
Awareness of how to take a GenAI POC into a scalable, production-ready system in a secure environment.
Benefit packages for this role will start on the 31st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.