- Company Name
- Richdale AI
- Job Title
- AI Systems Engineer
- Job Description
-
**Job title:** AI Systems Engineer
**Role Summary:**
Design, fine‑tune, and deploy large language model (LLM) and agent‑based systems into production environments. Translate abstract AI concepts into scalable, reliable, and business‑critical applications while ensuring optimal performance, latency, and cost.
**Expectations:**
* Deliver end‑to‑end AI solutions that meet business requirements.
* Maintain high standards of code quality, observability, and security.
* Continuously improve model performance and system efficiency.
**Key Responsibilities:**
1. Design, fine‑tune, evaluate, and deploy LLMs (open‑source and proprietary).
2. Build and orchestrate AI agents (reasoning, decision support, automation) using frameworks such as LangChain or LlamaIndex.
3. Develop Retrieval‑Augmented Generation (RAG) pipelines, embeddings, vector search, and tool‑calling workflows.
4. Convert prototypes into production‑grade services with monitoring, logging, and alerting.
5. Collaborate with product, data, and cross‑functional teams to translate requirements into AI solutions.
6. Optimize models for latency, throughput, and cost in cloud or on‑premise environments.
7. Contribute to MLOps pipelines (CI/CD, model versioning, deployment, observability).
8. Stay current on AI research and apply practical advancements.
**Required Skills:**
* 2–5 years of experience in AI / ML or software engineering.
* Strong proficiency in Python and solid software engineering fundamentals.
* Hands‑on experience with LLM fine‑tuning, prompting, and evaluation.
* Familiarity with agent frameworks (LangChain, LlamaIndex, etc.).
* Experience with vector databases (FAISS, Pinecone, Weaviate, etc.).
* Understanding of API‑based model deployment and cloud platforms (AWS, GCP, Azure).
* Ability to ship prototypes to production with monitoring and logging.
**Nice to Have:**
* MLOps tools (MLflow, Weights & Biases, Kubeflow, etc.).
* Knowledge of NLP or computer vision.
* Experience deploying AI in enterprise or operational settings.
* Cost‑optimization and scalability skills for LLM systems.
**Required Education & Certifications:**
* Bachelor’s or higher degree in Computer Science, Data Science, Machine Learning, or a related technical field.
* Relevant certifications (e.g., AWS Certified Machine Learning, Google Cloud ML Engineer) are a plus.