Generative AI Engineer

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. 

Qualifications :

Responsibilities  

• 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. 

Must Have 

• Education: Masters 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 

Tools & Technologies 

• 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 

Additional Information :

What We Offer 

• 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 

Afficiency is an Equal Opportunity Employer. All your information will be kept confidential according to EEO guidelines.

Remote Work :

No

Employment Type :

Full-time