Llm Application Development Engineer Jobs

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1d ago

Senior Generative AI Engineer

Cogniify San Francisco Bay Area, CA

San Francisco Bay Area, CA

1d ago

$150k - $170k/yr Full time Senior Agentic Ai Ai Agent

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Job Description

Cogniify is seeking a hands-on Senior Generative AI Engineer to design, build, and deploy production-grade AI applications. The role focuses on LLM-powered products, RAG pipelines, and intelligent agent workflows, using Python alongside cloud infrastructure.

Role Focus

Design and develop scalable LLM-powered applications in Python
Build RAG pipelines using document processing, embeddings, vector databases, semantic search, and reranking
Develop AI-agent and multi-agent workflows with tool calling, memory, orchestration, and human approval steps
Integrate LLMs with internal systems, external APIs, databases, and enterprise applications

Key Responsibilities

Evaluate and select foundation models based on accuracy, latency, cost, security, and business needs
Improve prompt quality, retrieval accuracy, response time, and token usage
Implement safety guardrails, output validation, access controls, and fallback mechanisms
Create automated evaluation frameworks to measure response quality, hallucination, relevance, and reliability
Containerize applications with Docker and deploy on AWS, Azure, or GCP
Apply monitoring and LLMOps practices for model performance, cost, latency, errors, and production usage
Collaborate with product, engineering, and business teams to translate requirements into reliable AI solutions
Document technical architecture, design decisions, APIs, and operational processes

Required Qualifications

Bachelor’s or Master’s degree in Computer Science, Engineering, or a related discipline, or equivalent practical software-development experience
6-9 years of professional software-development experience, including strong hands-on experience with Python
Experience developing backend services and integrating REST APIs
Hands-on experience building LLM or Generative AI applications
Practical experience implementing RAG using embeddings, semantic search, and vector databases
Experience with LangChain, LangGraph, LlamaIndex, or a comparable LLM application framework
Experience integrating foundation models through APIs such as OpenAI, Anthropic Claude, Gemini, or Azure OpenAI
Working knowledge of vector databases including Pinecone, Weaviate, Milvus, Qdrant, Chroma, FAISS, or pgvector
Experience with Docker and deployment on at least one cloud platform: AWS, Azure, or GCP
Understanding of prompt engineering, hallucination reduction, output validation, and LLM evaluation
Strong understanding of software engineering practices including Git, testing, debugging, and clean code
Ability to communicate technical solutions clearly to technical and non-technical stakeholders

Technologies and Tools

Python, Retrieval-Augmented Generation (RAG), embeddings, semantic search, reranking
Frameworks: LangChain, LangGraph, LlamaIndex
Model providers/APIs: OpenAI, Anthropic Claude, Gemini, Azure OpenAI
Vector databases: Pinecone, Weaviate, Milvus, Qdrant, Chroma, FAISS, pgvector
Cloud and DevOps: Docker, AWS, Azure, GCP, Kubernetes, CI/CD pipelines
ML/Serving and ecosystems: Hugging Face Transformers, PyTorch, LoRA, QLoRA, vLLM, TGI, Ollama
Observability/LLMOps: LangSmith, Langfuse, Arize Phoenix, MLflow, Weights & Biases
Agent frameworks: AutoGen, CrewAI, Semantic Kernel

Benefits

Unlimited PTO
Very generous parental leave, above industry standards
Entrepreneurial culture with frequent experimentation and risk-taking
Open communication with management and company leadership
Small, dynamic teams with high impact
Medical, Dental and Vision coverage for employees
Access to Disability & Life insurance
Mental health and wellbeing support
Annual bonus program
Employer Stock Purchase Program (ESPP)
Yearly team building experiences
Mentorship and sponsorship opportunities
Manager resources and support

What Success Looks Like

Production-ready AI applications that are accurate, secure, and maintainable
RAG systems that retrieve relevant information and reduce hallucinations
AI-agent workflows that reliably complete business tasks and integrate with existing systems
Measurable improvements in response quality, latency, and inference cost
Clear monitoring of application performance, usage, errors, and model behaviour

Location and Compensation

Location: Hybrid remote in the San Francisco Bay Area, CA
Salary: USD 150,000 - 170,000 per year
Salary range note: US East/West Coast: $150000 - $170000

Education

Bachelor’s or Master’s degree in Computer Science, Engineering or a related discipline.

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