Generative AI Engineer

Afficiency Inc.
New York, United States of America
3 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Intermediate
Compensation
$ 120K

Job location

New York, United States of America

Tech stack

API
Artificial Intelligence
Amazon Web Services (AWS)
Automated Storage and Retrieval Systems
Audit Trail
Azure
Cloud Computing
Information Engineering
Data Security
Elasticsearch
Python
Machine Learning
Regression Testing
Software Engineering
Privacy Controls
Reinforcement Learning
Data Logging
Data Ingestion
Flask
Large Language Models
Snowflake
Generative AI
Rate Limiting
FastAPI
Kubernetes
Wikis
Machine Learning Operations
Terraform
GPT
Docker
Databricks

Job description

As a Generative AI Engineer at Afficiency, you will be responsible for designing, developing and deploying Generative AI solutions that enhance our core product platforms and client implementations. You will work closely with engineering, data science, and infrastructure teams to build scalable AI-driven applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), model fine-tuning, and reinforcement learning approaches.

This role is ideal for someone who is based in the NYC Metro Area, passionate about building real-world GenAI applications and bringing them into production, while continuously improving performance, reliability, and user outcomes., * Deliver GenAI solutions end-to-end

  • Own technical design and implementation of GenAI applications from discovery through production handoff.
  • Build APIs/services that integrate with enterprise systems and analytics platforms.
  • Implement enterprise-grade RAG
  • Design ingestion pipelines for internal content (PDFs, policies, research, dashboards, ticketing, wikis).
  • Build retrieval systems with hybrid search, filtering, re-ranking, query rewriting, and context optimization.
  • Implement permission-aware retrieval aligned to entitlements and data access policies.
  • Establish evaluation and quality controls.
  • Define metrics for retrieval quality and answer grounding (faithfulness, citation accuracy, coverage).
  • Create golden datasets, regression tests, and automated evaluation harnesses.
  • Operationalize GenAI (LLMOps)
  • Instrument observability (latency, cost, token usage, error rates) and implement safe rollout patterns.
  • Implement caching, rate limiting, fallbacks, and incident-ready operational practices.
  • Partner across teams to land solutions
  • Collaborate with business owners to translate requirements into workable designs.
  • Work with Security/Compliance to embed guardrails, auditability, and privacy controls.
  • Provide clear documentation and implementation of playbooks to enable internal teams' post-engagement., * LLM frameworks: LangChain, LlamaIndex, Semantic Kernel (optional)
  • Vector/hybrid search: Open to different skillsets
  • Data: (Snowflake/Databricks/warehouse), event pipelines, document stores
  • Observability: logging/tracing/metrics, dashboards, alerting

Requirements

  • Education: Master's degree or equivalent experience required
  • 3+ years in software engineering, data engineering, ML engineering, or applied AI, including recent GenAI delivery in production.
  • Demonstrated expertise in RAG system design and optimization, including:
  • chunking + metadata enrichment, hybrid search, re-ranking, retrieval evaluation
  • grounding/citations and hallucination mitigation patterns
  • Strong Python and backend engineering skills (FastAPI/Flask), plus strong SQL.
  • Experience working in regulated or security-conscious environments, with knowledge of:
  • access controls/entitlements, data privacy, logging/audit trails, secure SDLC practices
  • Proven ability to work effectively as an IC consultant:
  • communicate architecture decisions clearly
  • influence cross-functional stakeholders without direct authority produce high-quality documentation and handoff materials

Nice to Have

  • Fine-tuning experience (SFT, LoRA/QLoRA) and familiarity with preference optimization concepts (DPO/RLHF)
  • Vector/hybrid search platforms: Elasticsearch/OpenSearch vector, FAISS, Pinecone, Weaviate, Milvus
  • LLMOps tooling: MLflow/W&B, OpenTelemetry, prompt registries, evaluation frameworks
  • Cloud + platform: AWS/Azure/GCP, Docker/Kubernetes, Terraform

Benefits & conditions

Pulled from the full job description 401(k) matching Paid time off Vision insurance Dental insurance Life insurance, * Competitive salary with equity options

  • Robust health, dental, and vision benefits for employee and dependents
  • 401k matching contributions
  • Generous PTO policy
  • Provided work-from-home equipment

About the company

Afficiency is a rapidly growing Insurtech startup whose mission is to provide life insurance to everyone on the platforms they already trust. Located in NYC, we design life insurance products that can be purchased entirely digitally and can be easily embedded into distribution platforms or with agents who sell insurance. The company is experiencing rapid growth and is well-funded. We are looking for new team members to join us on our journey to shake up the life insurance industry. We need individuals who bring passion, curiosity, and a desire for excellence.

Apply for this position