Generative AI Engineer (Data / ML / GenAI) (Jersey City)

Generative Ai Engineer (Data / Ml / Genai)

We're hiring a Generative AI Engineer with 6+ years across Data / ML / GenAI who can design, build, and productionize LLM-powered systems end-to-end. You'll select and fine-tune models (OpenAI, Anthropic, Google, Meta, open-source), craft robust RAG / agentic workflows (AutoGen, LangGraph, CrewAI, LangChain / LlamaIndex), and ship secure, observable services with FastAPI, Docker, and Kubernetes. You pair strong software engineering with MLOps / LLMOps rigorevaluation, monitoring, safety / guardrails, and cost / latency optimization.

Key Responsibilities

• Own E2E design for chat / agents, structured generation, summarization / classification, and workflow automation. Choose the right model vs. non-LLM alternatives and justify trade-offs.
• Build prompt stacks (system / task / tool), synthetic data pipelines, and fine-tune or LoRA adapters; apply instruction tuning / RLHF where warranted.
• Implement multi-agent / tool-calling workflows using AutoGen, LangGraph, CrewAI (state management, retries, tool safety, fallbacks, grounding).
• Stand up retrieval stacks with vector DBs (Pinecone / Faiss / Weaviate / pgvector), chunking and citation strategies, reranking, and caching; enforce traceability.
• Ship FastAPI services, containerize (Docker), orchestrate (Kubernetes / Cloud Run), wire CI / CD and IaC; design SLAs / SLOs for reliability and cost.
• Instrument evals (unit / regression / AB), add tracing and metrics (Langfuse, LangSmith, OpenTelemetry), and manage model / version registries (MLflow / W&B).
• Implement guardrails (prompt injection / PII / toxicity), policy filters (Bedrock Guardrails / Azure AI Content Safety / OpenAI Moderation), access controls, and compliance logging.
• Build / maintain data ingestion, cleansing, and labeling workflows for model / retrieval corpora; ensure schema / version governance.
• Optimize with batching, streaming, JSON-schema / function calling, tool-use, speculative decoding / KV caching, and token budgets.
• Partner with product / engineering / DS; review designs / PRs, mentor juniors, and drive best practices / playbooks.

Preferred Qualifications

Nice to Have

Prior work in data-heavy or regulated domains (finance / health / gov) with auditable GenAI outputs.

Requirements