Senior AI Engineer in Los Angeles

Energy Jobline
Los Angeles, CA, United States
7 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
2 years minimum
Working hours
Regular working hours

Tech stack

Artificial Intelligence BigQuery Continuous Integration Information Engineering Distributed Data Store Github Python (Programming Language) Performance Tuning Prometheus SQL Databases Parquet Data Storage Management
+15 more
Enterprise Software Applications Feature Engineering Autoscaling Large Language Models Grafana Apache Spark Generative AI Git Kubernetes Information Technology Avro Apache Kafka Machine Learning Operations Docker Microservices

Job description

Our client is a family office management company serving investments, foundations, and activities of a prominent family. With a broad mandate, their organization oversees diverse assets and programs, including multiple foundations and institutes. Across their entities, they manage hundreds of employees and oversee significant annual expenditures, ranging from grants and gifts to private investments and operational costs., You will architect and develop production-grade LLM agents and RAG pipelines, steer the full ML lifecycle from data prep to GPU-scaled deployment, and weave together modern tools and technologies into a secure, cost-aware platform. If you thrive on turning ambiguous ideas into high-impact GenAI products and mentoring others to do the same, this is your playground.Responsibilities:

  • Build & Ship Gen AI Apps: Design, prototype, and build GenAI solutions, RAG document pipelines, and task-specific agents to support multiple business functions using tools such as LangChain/LlamaIndex, micro-services, Ray/KubeRay.
  • Agent Workflow Pipelines: Design and orchestrate multi-step agent pipelines, integrating LLM prompts, external APIs, and human-in-the-loop escalations.
  • End-to-End ML Lifecycle: Own requirements * data prep * feature engineering * classical ML or LLM fine-tuning (LoRA, PEFT, RLHF) * offline/online evaluation * MLflow registry, with automated drift and quality alerts.
  • Data & Storage Architecture: Ingest from BigQuery, object-store lakes (Parquet, Avro); generate embeddings and persist to vector DBs (Qdrant/PgVector); enforce governance via OpenMetadata and column-level ACLs.
  • Scalable Deployment & Ops: Package with Docker, helm-deploy on Kubernetes; implement GPU scheduling, autoscaling, blue-green rollouts, and cost telemetry via Prometheus/Grafana; automate CI/CD in GitHub Actions.
  • Observability & Compliance: Instrument tracking, metrics, and structured logs; run A/B or shadow tests; embed security, privacy, and cost-guardrails in every pipeline.
  • Lead & Mentor: Translate ambiguous business ideas into executable roadmaps, run build-vs-buy analysis, set code standards, and coach peers on agentic patterns and ethical AI.

Requirements

They are seeking a highly motivated, innovative, and collaborative Technology staff member to serve as the Senior AI Engineer. The selected candidate will be a member of the Enterprise Technology Data Engineering & AI team, playing a pivotal role in driving innovation across the organization., * Bachelor’s or Master’s in Computer Science, Data Science, or equivalent experience.

  • 7+ years designing and shipping ML/AI applications, including 2+ years with LLMs or Generative AI.
  • Demonstrated delivery of RAG or agentic systems in production (e.g. LangChain, LlamaIndex, n8n, or custom).
  • Expert-level Python and SQL; strong Spark, distributed data-processing, and performance-tuning skills.
  • Hands-on fine-tuning of foundation models; comfort with MLflow, Ray/KubeRay, and vector databases.
  • Deep familiarity with cloud warehouses (BigQuery, Redshift), lake formats (Parquet, Avro), and streaming/ingestion tools (e.g. Airbyte, Kafka/Pub-Sub).
  • Production experience with Docker, Kubernetes, Helm, and Git-based CI/CD pipelines.
  • Clear communicator able to gather requirements, set technical direction, and influence cross-functional teams.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on www.energyjobline.com

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

2:08 min

Essential engineering roles in the generative AI space

Mary Grygleski Mary Grygleski · LIVE

2:07 min

Inspecting default bridge architectures and custom Docker networks

Oliver Seitz Oliver Seitz · WWC 2025

3:02 min

Audience Q&A on data formats and engine tradeoffs

Matthias Niehoff Matthias Niehoff · WWC Europe 2026

6:21 min

Investigating push inefficiencies with upstream Git experts

Jonathan Creamer · Coffee With Developers

2:34 min

Docker sandbox architecture and microVM environment integration

Manuel de la Peña Manuel de la Peña · WWC Europe 2026

1:52 min

Customizing block storage tiers and formats

Ricardo Sueiras Sueiras · LIVE

Videos

See all

Related articles

See all